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==ВАК-овские журналы по тематике Ресурса== В списке ниже приведены некоторые из журналов (в основном зарубежных) таких, что по тематике они попадают в одно или несколько [[:Категория:Научные направления|научных направлений]] Ресурса и публикации в них признаются [[ВАК]]-ом при защите кандидатских и докторских диссертаций. Полный список(по всем тематикам) российских журналов, признаваемых ВАК можно [http://vak.ed.gov.ru/common/img/uploaded/files/vak/enumeration/per-04-2008-4.doc скачать с официального сайта ВАК]. Из зарубежных журналов по естественным наукам [http://vak.ed.gov.ru/ru/news/allnews/index.php?id4=896&from4=1&afrom=10.04.2008&ato=11.07.2008 ВАКом признаются] все журналы, входящие в систему цитирования Web of Science:Science Citation Index Expanded. Их полный список можно [http://science.thomsonreuters.com/mjl/wos_scie_a5021_final.pdf скачать здесь]. В большинстве журналов публикация, принятая к печати, выходит как в электронном, так и в бумажном виде, в список Science Citation Index Expanded входят только ISSN бумажных вариантов. В списке ниже для журналов приведены: ISSN (в том числе электронной версии), периодичность выхода, impact factor ([http://ru.wikipedia.org/wiki/%D0%98%D0%BC%D0%BF%D0%B0%D0%BA%D1%82_%D1%84%D0%B0%D0%BA%D1%82%D0%BE%D1%80 Что такое импакт-фактор.]) и краткая аннотация. У некоторых журналов публикации в электронном виде доступны бесплатно (можно найти по ссылкам на сайт журнала), у некоторых бесплатно доступны старые публикации и практически у всех журналов электронные публикации доступны по подписке. Некоторые журналы являются преимущественно электронными, но даже у них с некоторой периодичностью все статьи публикуются в виде бумажных сборников. Пропуски в полях списка означают, что соответствующая информация не была найдена. Если вы можете дополнить информацию или список журналов - сделайте это пожалуйста! ===Подборки журналов=== * [https://docs.google.com/document/d/1Ho1vTo8muo5RNQJ7IgAGULuRp6pnth-lJutaxXxm8o0/pub Список журналов, рекомендованных отделом Интеллектуальных систем] * [https://docs.google.com/document/d/1v_sdw28BP2z26JVY2naHOv_oIbn0y16DRIcPKXgKpaQ/pub Список журналов по экспертным системам\text mining] * [https://docs.google.com/spreadsheet/ccc?key=0AqZWpNtugyPHdC13MmkxTUxuWnRTM0h4aDZwbDNQUXc&usp=drive_web#gid=0 Список журналов для техничсеких публикаций] * [https://docs.google.com/document/d/1hcvtJJRXJpZ2wR8utleVhPoW8xDkHXW2KZ4v6Wzey1w/pub Список журналов для публикаций с ключевыми словами акселерометер и нейросеть] * [https://docs.google.com/document/d/1568mWA9h7CmDqsErsBQKKBZBoWTs0N9c02C9QrtsUvY/pub Журналы с высоким импакт-фактором] ===Машинное обучение и вычислительная математика=== {| class=standard" | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.maik.ru/cgi-perl/journal.pl?name=vychmat&lang=rus Журнал Вычислительной Математики И Математической Физики]''' | '''0044-4669''' | | '''12''' | | '''Осипов Ю.С.''' |- | colspan="6" | Вычислительная математика и математическая физика – ежемесячный периодический журнал Российской Академии наук, основанный в 1961 г. академиком А.А. Дородницыным. В журнале публикуются обзоры и оригинальные исследования в области вычислительной математики, численных методов математической физики, информатики, и других математических дисциплин. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://jmlr.csail.mit.edu/ Journal Of Machine Learning Research]''' | '''1532-4435''' | '''1533-7928''' | '''8 ''' | | '''Lawrence Saul Leslie Pack Kaelbling''' |- | colspan="6" | The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR seeks previously unpublished papers on machine learning that contain: * new algorithms with empirical, theoretical, psychological, or biological justification; * experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems; * accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods; * formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks; * development of new analytical frameworks that advance theoretical studies of practical learning methods; * computational models of data from natural learning systems at the behavioral or neural level; or * extremely well-written surveys of existing work. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/artificial/journal/10994 Machine Learning]''' | '''0885-6125''' | '''1573-0565''' | | '''1.742''' | |- | colspan="6" | Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems, including but not limited to: Learning Problems: Classification, regression, recognition, and prediction; Problem solving and planning; Reasoning and inference; Data mining; Web mining; Scientific discovery; Information retrieval; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and control; Combinatorial optimization; Game playing; Industrial, financial, and scientific applications of all kinds. Learning Methods: Supervised and unsupervised learning methods (including learning decision and regression trees, rules, connectionist networks, probabilistic networks and other statistical models, inductive logic programming, case-based methods, ensemble methods, clustering, etc.); Reinforcement learning; Evolution-based methods; Explanation-based learning; Analogical learning methods; Automated knowledge acquisition; Learning from instruction; Visualization of patterns in data; Learning in integrated architectures; Multistrategy learning; Multi-agent learning. |} ===Анализ данных=== {| class=standard" | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/database+management+%26+information+retrieval/journal/10618 Data Mining And Knowledge Discovery]''' | '''1384-5810''' | '''1573-756X''' | | '''2.42''' | '''Geoffrey I. Webb''' |- | colspan="6" | Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.<br /><br />KDD is concerned with issues of scalability, the multi-step knowledge discovery process for extracting useful patterns and models from raw data stores (including data cleaning and noise modelling), and issues of making discovered patterns understandable.<br /><br />Data Mining and Knowledge Discovery is the premier technical publication in the field, providing a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities. The journal publishes original technical papers in both the research and practice of DMKD, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. Short (2-4 pages) application summaries are published in a special section.<br /><br />The journal accepts paper submissions of any work relevant to DMKD. A summary of the scope of Data Mining and Knowledge Discovery includes:<br /><br />'''Theory and Foundational Issues''': Data and knowledge representation; modelling of structured, textual, and multimedia data; uncertainty management; metrics of interestingness and utility of discovered knowledge; algorithmic complexity, efficiency, and scalability issues in data mining; statistics over massive data sets.<br /><br />'''Data Mining Methods''': including classification, clustering, probabilistic modelling, prediction and estimation, dependency analysis, search, and optimization.<br /><br />Algorithms for data mining including spatial, textual, and multimedia data (e.g., the Web), scalability to large databases, parallel and distributed data mining techniques, and automated discovery agents.<br /><br />'''Knowledge Discovery Process''': Data pre-processing for data mining, including data cleaning, selection, efficient sampling, and data reduction methods; evaluating, consolidating, and explaining discovered knowledge; data and knowledge visualization; interactive data exploration and discovery.<br /><br />'''Application Issues''': Application case studies; data mining systems and tools; details of successes and failures of KDD; resource/knowledge discovery on the Web; privacy and security issues. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.iospress.nl/html/1088467x.php Intelligent Data Analysis] ''' | '''1088-467X''' | | '''6''' | | '''A. Famili ''' |- | colspan="6" | Intelligent Data Analysis provides a forum for the examination of issues related to the research and applications of Artificial Intelligence techniques in data analysis across a variety of disciplines. These techniques include (but are not limited to): all areas of data visualization, data pre-processing (fusion, editing, transformation, filtering, sampling), data engineering, database mining techniques, tools and applications, use of domain knowledge in data analysis, machine learning, neural nets, fuzzy logic, statistical pattern recognition, evolutionary algorithms, knowledge filtering, and post-processing. In particular, we prefer papers that discuss development of new AI related data analysis architectures, methodologies, and techniques and their applications to various domains. Papers published in this journal are geared heavily towards applications, with an anticipated split of 70% of the papers published being applications-oriented, research and the remaining 30% containing more theoretical research. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.inderscience.com/browse/index.php?Journalid=189 International Journal Of Data Mining And Bioinformatics]''' | '''1748-5673''' | '''1748-5681''' | '''4''' | | '''Xiaohua (Tony) Hu''' |- | colspan="6" | IJDMB aims to publish the latest research and development results and experiences in the areas of bioinformatics, data mining and knowledge discovery, and the role of data mining techniques and methods in integrating and interpreting the bioinformatics data sets and improving effectiveness and/or efficiency and quality for bioinformatics data analysis. The major objective of IJDMB is to stimulate new multidisciplinary research and the development of cutting-edge data mining methods, techniques and tools to solve problems in bioinformatics. The goal is to help readers understand state-of-the-art techniques/algorithms/methods in bioinformatics data gathering, data pre-processing, data mining and data management. Topics of interest include but not limited to: * Biological data pre-processing and cleaning * Biological data visualisation * Biological data integration and management * Phylogenetics * Biomedical ontologies construction/management * Microarray data analysis * Protein/RNA structure prediction * Genomics and proteomics * Drug design * Biomedical literature data mining * Modelling of biomolecular pathways * Whole, multiple genome comparison * Systems biology and pathways * Biological data curation |} ===Распознавание образов и анализ изображений=== {| class=standard" | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.maik.ru/journals/patrec.htm Pattern Recognition And Image Analysis: Advances In Mathematical Theory And Applications]''' | '''1054-6618''' | '''1555-6212''' | '''4''' | | '''Журавлёв Ю. И.''' |- | colspan="6" | Международный журнал Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications (Распознавание образов и анализ изображений. Успехи в области математической теории и приложений) публикует, главным образом, наиболее существенные оригинальные работы в области распознавания образов, распознавания, анализа, понимания и обработки изображений и смежных областей теоретической и прикладной информатики. Это единственное периодическое издание по данной тематике в странах бывшего СССР, восточной и центральной Европы. Главный редактор журнала - академик РАН Ю.И.Журавлев. В редколлегию входят ведущие российские и зарубежные ученые в указанных областях. Авторами журнала являются видные ученые и специалисты в области фундаментальных и прикладных исследований в области теоретической и прикладной информатики. Основными разделами журнала являются математическая теория распознавания образов и анализа изображений, методы и средства представления информации в задачах распознавания, машинное зрение, обработка, анализ и понимание изображений, машинное обучение, машинная графика, прогнозирование, информационные технологии, базы данных, базы знаний, программные средства, специализированные вычислительные архитектуры, ориентированные на задачи распознавания образов и анализа изображений, прикладные задачи, нейронные сети. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://ieeexplore.ieee.org/xpl/recentissue.jsp?punumber=34 IEEE Transactions On Pattern Analysis And Machine Intelligence]''' | '''0162-8828''' | | '''12''' | | '''Ramin Zabih''' |- | colspan="6" | The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope. This includes all traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence. Areas of such machine learning, search techniques, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, face and gesture recognition and relevant specialized hardware and/or software archictectures are also covered. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/computer+imaging/journal/10032 International Journal On Document Analysis And Recognition]''' | '''1433-2833 ''' | '''1433-2825''' | | | '''K. Tombre D.S. Doermann''' |- | colspan="6" | The large number of existing documents and the production of a multitude of new ones every year raise important issues in efficient handling, retrieval and storage of these documents and the information which they contain. This has led to the emergence of new research domains dealing with the recognition by computers of the constituent elements of documents - including characters, symbols, text, lines, graphics, images, handwriting, signatures, etc. In addition, these new domains deal with automatic analyses of the overall physical and logical structures of documents, with the ultimate objective of a high-level understanding of their semantic content. We have also seen renewed interest in optical character recognition (OCR) and handwriting recognition during the last decade. Document analysis and recognition are obviously the next stage. Automatic, intelligent processing of documents is at the intersections of many fields of research, especially of computer vision, image analysis, pattern recognition and artificial intelligence, as well as studies on reading, handwriting and linguistics. Although quality document related publications continue to appear in journals dedicated to these domains, the community will benefit from having this journal as a focal point for archival literature dedicated to document analysis and recognition. This journal publishes articles of four primary types - original research papers, correspondence, overviews and summaries, and research notes. Special issues on active areas of research are encouraged. We welcome submissions in all areas related to document analysis and recognition. Possible topics include: - Document Image Processing - Document Models - Handwriting Models and Analysis - Character and Word Recognition - On-line Recognition - Pen Based Computing - Multi-lingual Processing - Physical and Logical Analysis - Graphics Recognition - Map and Line Drawing Understanding - Storage and Retrieval of Documents - Text Analysis and Processing - Natural Language Issues - Information Extraction and Filtering - Performance Evaluation - Document Authentification and Validation - Implementations, Applications and Systems as well as non-traditional topics such as: - Processing Text in Other Contexts - Multimedia and Hypermedia Analysis - Time Varying Documents - Distributed Document Collections (Digital Libraries). |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.worldscinet.com/ijprai/ijprai.shtml International Journal Of Pattern Recognition And Artificial Intelligence] ''' | '''0218-0014''' | '''1793-6381''' | | | '''X Jiang P S P Wang''' |- | colspan="6" | This journal publishes both applications and theory-oriented articles on new developments in the fields of pattern recognition and artificial intelligence, and is of interest to both researchers in industry and academia. From the beginning, there has always been a close relationship between the disciplines of pattern recognition and artificial intelligence. The recognition and understanding of sensory data like speech or images, which are major concerns in pattern recognition, have always been considered as important subfields of artificial intelligence. On the other hand, topics like knowledge representation, inference, search or learning that belong to the center of artificial intelligence, have constantly attracted the attention of researchers working in pattern recognition. IJPRAI is the first to cover both fields in one periodical, and particular emphasis is put on papers which are in the intersection of both fields. However, it is open to articles from "pure" pattern recognition and "pure" artificial intelligence as well. * Contains current material on applications and theory research in: o Image Processing o Natural Language Processing o Computer Vision o Speech Understanding o Pattern Recognition o Robotics and Related Fields o Expert Systems o Artificial Intelligence o Knowledge Engineering o Neural Networks * Has special issues devoted to relevant and key areas in the field * Is a worthwhile investment for researchers/libraries concerned with research in industry or academia |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/328/description#description Pattern Recognition]''' | '''0031-3203''' | | '''12''' | '''2.019''' | '''Ching Y. Suen''' |- | colspan="6" | Pattern Recognition is the official journal of the Pattern Recognition Society. The Society was formed to fill a need for information exchange among research workers in the pattern recognition field. Up to now, we ''pattern-recognitionophiles'' have been tagging along in computer science, information theory, optical processing techniques, and other miscellaneous fields. Because this work in pattern recognition presently appears in widely spread articles and as isolated lectures in conferences in many diverse areas, the purpose of the journal Pattern Recognition is to give all of us an opportunity to get together in one place to publish our work. The journal will thereby expedite communication among research scientists interested in pattern recognition. We consider pattern recognition in the broad sense, and we assume that the journal will be read by people with a common interest in pattern recognition but from many diverse backgrounds. These include biometrics, target recognition, biological taxonomy, meteorology, space science, classification methods, character recognition, image processing, industrial applications, neural computing, and many others. The publication policy is to publish (1) new original articles that have been appropriately reviewed by competent scientific people, (2) reviews of developments in the field, and (3) pedagogical papers covering specific areas of interest in pattern recognition. Various special issues will be organized from time to time on current topics of interest to Pattern Recognition. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/505619/description#description Pattern Recognition Letters]''' | '''0167-8655 ''' | | '''16''' | '''0.853''' | '''T.K. Ho G. Sanniti di Baja''' |- | colspan="6" | Pattern Recognition Letters aims at rapid publication of concise articles of a broad interest in pattern recognition. Subject areas include all the current fields of interest represented by the Technical Committees of the International Association of Pattern Recognition, and other developing themes involving learning and recognition. Examples include: • statistical, structural, syntactic pattern recognition; • neural networks, machine learning, data mining; • discrete geometry, algebraic, graph-based techniques for pattern recognition; • signal analysis, image coding and processing, shape and texture analysis; • computer vision, robotics, remote sensing; • document processing, text and graphics recognition, digital libraries; • speech recognition, music analysis, multimedia systems; • natural language analysis, information retrieval; • biometrics, biomedical pattern analysis and information systems; • scientific, engineering, social and economical applications of pattern recognition; • special hardware architectures, software packages for pattern recognition. We invite contributions as research reports or commentaries. Research reports should be concise summaries of methodological inventions and findings, with strong potential of wide applications. Alternatively, they can describe significant and novel applications of an established technique that are of high reference value to the same application area and other similar areas. Commentaries can be lecture notes, subject reviews, reports on a conference, or debates on critical issues that are of wide interests. To serve the interests of a diverse readership, the introduction should provide a concise summary of the background of the work in an accepted terminology in pattern recognition, state the unique contributions, and discuss broader impacts of the work outside the immediate subject area. All contributions are reviewed on the basis of scientific merits and breadth of potential interests. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/computer+imaging/journal/10044 Pattern Analysis And Applications]''' | '''1433-7541''' | '''1433-755X''' | | '''0.515''' | '''Sameer Singh''' |- | colspan="6" | The journal publishes high quality articles in areas of fundamental research in intelligent pattern analysis and applications in computer science and engineering. It aims to provide a forum for original research which describes novel pattern analysis techniques and industrial applications of the current technology. In addition, the journal will also publish articles on pattern analysis applications in medical imaging. The journal solicits articles that detail new technology and methods for pattern recognition and analysis in applied domains including, but not limited to, computer vision and image processing, speech analysis, robotics, multimedia, document analysis, character recognition, knowledge engineering for pattern recognition, fractal analysis, and intelligent control. The journal publishes articles on the use of advanced pattern recognition and analysis methods including statistical techniques, neural networks, genetic algorithms, fuzzy pattern recognition, machine learning, and hardware implementations which are either relevant to the development of pattern analysis as a research area or detail novel pattern analysis applications. Papers proposing new classifier systems or their development, pattern analysis systems for real-time applications, fuzzy and temporal pattern recognition and uncertainty management in applied pattern recognition are particularly solicited. The journal encourages the submission of original case-studies on applied pattern recognition which describe important research in the area. The journal also solicits reviews on novel pattern analysis benchmarks, evaluation of pattern analysis tools, and important research activities at international centres of excellence working in pattern analysis. |} ===Искусственный интеллект=== {| class=standard" | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.intsys.msu.ru/magazine/ Интеллектуальные системы]''' | '''5-7281-0436-3''' | | | | '''В.Б. Кудрявцев''' |- | colspan="6" | В журнале "Интеллектуальные системы" (издается с 1996 г.) публикуются научные достижения в области теории и приложений интеллектуальных систем, новых информационных технологий и компьютерных наук. Издание журнала осуществляется под эгидой МГУ им. М.В. Ломоносова, Научного Совета по комплексной проблеме "Кибернетика" РАН, Отделения "Математические проблемы наукоемких технологий" АТН РФ, Секции "Информатики и кибернетики" РАЕН, МИРЭА, научно-учебного центра МГУ – ВЦ РАН – РГГУ "Интеллектуальные системы и нечеткие технологии" (ФЦП "Интеграция", проект И-0899/2139 "Математические исследования сложных систем", направление №3). В издании журнала участвуют: кафедра МаТИС МГУ, МНЦ КИТ, ЦНИТ МГУ, УНЦ РНУОМ РГГУ. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/artificial/journal/10472?Detailspage=aimsandscopes Annals Of Mathematics And Artificial Intelligence]''' | '''1012-2443''' | '''1573-7470''' | | '''0.588''' | '''Martin C. Golumbic''' |- | colspan="6" | The scope of Annals of Mathematics and Artificial Intelligence is intended to represent a wide range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to Artificial Intelligence areas as diverse as decision support, automated deduction, reasoning, knowledge-based systems, machine learning, computer vision, robotics and planning.<br /><br />The journal is aimed at: applied logicians, algorithms and complexity researchers, Artificial Intelligence theorists and applications specialists using mathematical methods.<br /><br />It is hoped to influence the spawning of new areas of applied mathematics and the strenghtening of the scientific underpinnings of Artificial Intelligence.<br /><br />Annals of Mathematics and Artificial Intelligence consists of collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages). These collections of papers will focus on one topic and will feature one or more guest editors.<br /><br />Potential guest editors are invited to submit their proposal to the Editor-in-Chief. Please note that collections on topics within intelligent systems that show a strong foundational component are strongly encouraged. All information regarding the contents of Annals of Mathematics and Artificial Intelligence should be addressed to the Editor-in-Chief. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.tandf.co.uk/journals/tf/08839514.html Applied Artificial Intelligence]''' | '''0883-9514''' | '''1087-6545''' | '''10''' | '''0.753''' | '''Robert Trappl''' |- | colspan="6" | Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/505601/description#description Artificial Intelligence]''' | '''0004-3702 ''' | | '''18''' | '''3.008''' | '''C.R. Perrault A. G. Cohn''' |- | colspan="6" | Artificial Intelligence, which commenced publication in 1970, is now the generally accepted international forum for the publication of results of current research in this field. The journal welcomes basic and applied papers describing mature work involving computational accounts of aspects of intelligence. Specifically, it welcomes papers on: • automated reasoning • computational theories of learning • heuristic search • knowledge representation • qualitative physics • signal, image and speech understanding • robotics • natural language understanding • software and hardware architectures for AI. The journal reports results achieved; proposals for new ways of looking at AI problems must include demonstrations of effectiveness. From time to time, the journal publishes survey articles. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/505627/description#description Artificial Intelligence In Medicine]''' | '''0933-3657''' | | '''9''' | '''1.825''' | '''K.- P. Adlassnig''' |- | colspan="6" | Artificial Intelligence in Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, human biology, and health care. Particular attention is given to: • AI-based clinical decision making • medical knowledge engineering • knowledge-based and agent-based systems • computational intelligence in bio- and clinical medicine • intelligent medical information systems • AI in medical education • intelligent devices and instruments • automated reasoning and metareasoning in medicine • methodological, philosophical, ethical, and social issues of AI in medicine AIIM features: • original research contributions • methodological reviews • survey papers • special issue articles • position papers • historical perspectives • editorials • guest editorials • letters to the editor • book reviews |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/computer/artificial/journal/10462 Artificial Intelligence Review]''' | '''0269-2821''' | '''1573-7462''' | | '''0.634''' | '''David Robertson''' |- | colspan="6" | Artificial Intelligence Review serves as a forum for the work of researchers and application developers from Artificial Intelligence, Cognitive Science and related disciplines. The Review publishes state-of-the-art research reports and critical evaluations of applications, techniques and algorithms from these fields. Artificial Intelligence Review also presents refereed survey and tutorial articles, as well as reviews and commentary on significant developments from these disciplines. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.wiley.com/bw/aims.asp?ref=0824-7935&site=1 Computational Intelligence] ''' | '''0824-7935 ''' | '''1467-8640''' | '''4''' | '''1.972''' | '''Ali Ghorbani, Evangelos Milios''' |- | colspan="6" | This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research. FOCAL TOPICS OF COMPUTATIONAL INTELLIGENCE Machine learning - including in particular symbolic multistrategy and cognitive learning. Multistrategy learning systems integrate two or more inference types and/or representational mechanisms. These systems take advantage of the strengths of individual learning strategies, and therefore can be applied to a wider range of problems. Human learning is clearly not limited to any single strategy, but can involve any type of strategy, or a combination of them, depending on the task at hand. Research on multistrategy learning is therefore key to understanding learning processes in general, to making progress in machine learning, as well as to extending the applicability of current machine learning methods to new practical domains. Web intelligence and semantic web. Web intelligence is concerned with the application of AI to the next generation of web systems, services and resources. These include better search/retrieval algorithms, client side systems (e.g. more effective agents) and server side systems (e.g. effective ways to present material on web pages and throughout web sites, including adaptive websites and personalized interfaces). The semantic web is an extension to the World Wide Web, in which web content is expressed in a form that is accessible to programs (software agents), following the vision of the web as universal medium for data, information and knowledge exchange. Discovery science and knowledge mining. Discovery science (also known as discovery-based science) is a scientific methodology which emphasizes analysis of large volumes of experimental data or text data with the goal of finding new patterns or correlations, leading to hypothesis formation and other scientific methodologies. Tools of interest include: Data Mining: looking for associations or relationships in operational or transactional data; Text Mining and Information Extraction: looking for concepts and their associations or relationships in natural language text; Structured, semi-structured and unstructured text mining; Text Summarization: extracting terms and phrases from large text document collections that summarize their content; Web mining: Web structure, content and usage mining; Ontology Learning from Text and Data bases. Agents and multiagent systems. Agents as a computational abstraction have replaced "objects," and have provided the necessary ingredients to move to societies of interacting intelligent entities, based on things like the belief-desire-intention (BDI) model of agent societies, market economies, e-commerce models and game theory. Such abstractions are dispersed throughout the scientific world, depending largely on applications. Multiagent systems (MAS) are systems in which many intelligent autonomous agents interact with each other. Agents can be either cooperative, pursuing a common goal, or selfish, going after their own interests. Architectures, interaction protocols and languages must be developed for multiagent systems. Topics of interest include: Autonomy-oriented computing; Agent systems methodology and language; Agent-based simulation and modeling; Agent-based applications; Agent-based negotiation and autonomous auction; Distributed problem solving. Modern knowledge-based systems. Knowledge-based systems aim to make expertise available for decision making, and information sharing, when and where needed. The next generation of such systems needs to tap into large knowledge bases of domain-specific knowledge, which combine machine learning and structured background knowledge representation, such as ontology, and causal representations and reasoning. Information sharing is concerned with creating collaborative knowledge environments for sharing and disseminating information. Key application areas of AI. Entertainment and Gaming, Software Engineering, Business, Finance, Commerce and Economics, Knowledge-based and Personalized User Interfaces. We aim to make the journal the focus of key application areas, where AI is making a significant impact, but lack a coherent publication venue. These include: Entertainment and Game Development, i.e. building game engines using AI techniques; Software Engineering, including program understanding, software repositories and reverse engineering; Business, Finance, Commerce and Economics: learning aggregate behaviours (e.g. stock market trends) or modeling individual and group demographics (e.g. web mining); Knowledge-based and Personalized User Interfaces, to make interaction clearer to the user and more efficient, with better support for the users' goals, and efficient presentation of complex information. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/975/description#description Engineering Applications Of Artificial Intelligence]''' | '''0952-1976''' | | '''8''' | '''0.762''' | '''R.A. Vingerhoeds''' |- | colspan="6" | A journal of IFAC, the International Federation of Automatic Control Artificial Intelligence (AI) techniques are now being used by the practising engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering.Focal points ... click here for full Aims & Scope Artificial Intelligence (AI) techniques are now being used by the practising engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering. Focal points of the journal are: • Applications of real-time intelligent automation, and their associated supporting methodologies and techniques. • Architectures, algorithms and techniques for distributed AI systems. • Decision-support systems. • Aspects of reasoning: abductive, case-based, model-based, non-monotonic, incomplete, progressive and approximate reasoning. • Other theoretical aspects, e.g. chaos theory and fractals. • Knowledge processing, e.g. a priori and self-learning, knowledge elicitation and acquisition, knowledge representation, knowledge compaction, knowledge bases, expert systems, neural networks, fuzzy systems and genetic algorithms. • Perception, e.g. image and signal processing, pattern recognition, vision systems, tactile systems, and speech recognition and synthesis. • Aspects of software engineering, e.g. intelligent programming environments, the testing verification and validation of AI-based software, software and hardware architectures for the real-time use of AI techniques, safety and reliability. • Fault detection, fault analysis and diagnostics. • Industrial experiences in the application of the above techniques, e.g. case studies or bench-marking exercises. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://ieeexplore.ieee.org/xpl/recentissue.jsp?punumber=10207 IEEE Computational Intelligence Magazine]''' | '''1556-603X''' | | '''4''' | | '''Gary Yen ''' |- | colspan="6" | IEEE Computational Intelligence Magazine covers all areas of computational intelligence design and applications: applications oriented developments, successful industrial implementations, design tools, technology reviews, computational intelligence education, and applied research. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.worldscinet.com/ijait/ijait.shtml International Journal On Artificial Intelligence Tools]''' | '''0218-2130''' | '''1793-6349''' | '''6''' | | '''N. G. Bourbakis''' |- | colspan="6" | The International Journal on Artificial Intelligence Tools (IJAIT) provides an interdisciplinary forum in which AI scientists and professionals can share their research results and report new advances on AI tools or tools that use AI. Tools refer to architectures, languages or algorithms, which constitute the means connecting theory with applications. So, IJAIT is a medium for promoting general and/or special purpose tools, which are very important for the evolution of science and manipulation of knowledge. IJAIT can also be used as a test ground for new AI tools. Topics covered by IJAIT include but are not limited to: AI in Bioinformatics, AI for Service Engineering, AI for Software Engineering, AI for Ubiquitous Computing, AI for Web Intelligence Applications, AI Parallel Processing Tools (hardware/software), AI Programming Languages, AI Tools for CAD and VLSI Analysis/Design/Testing, AI Tools for Computer Vision and Speech Understanding, AI Tools for Multimedia, Cognitive Informatics, Data Mining and Machine Learning Tools, Heuristic and AI Planning Strategies and Tools, Image Understanding, Integrated/Hybrid AI Approaches, Intelligent System Architectures, Knowledge-Based/Expert Systems, Knowledge Management and Processing Tools, Knowledge Representation Languages, Natural Language Understanding, Neural Networks for AI, Object-Oriented Programming for AI, Reasoning and Evolution of Knowledge Bases, Self-Healing and Autonomous Systems, and Software Engineering for AI. IJAIT publishes high-quality, original research papers as well as state-of-the-art surveys related to AI tools on a bi-monthly basis in two types, full and short papers. It also publishes book reviews and brief updates on AI tools. Special issues related to the topics of the journal are welcome. A short proposal should be submitted to the Editor-in-Chief. It should include: a tentative title; name(s) and address(es) of the Guest Editor(s); purpose and scope; possible contributors; and a timetable (deadlines for "call for papers" and review processes, intended publication date, etc.) The whole process should take about a year. If the proposal is accepted, the Guest Editor(s) will be responsible for the special issue and should follow the normal IJAIT review process, which requires five reviewers for each received paper. Copies of the reviewed papers and the reviewers' comments should be given to the Editor-in-Chief for recording purposes. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.jair.org/ Journal Of Artificial Intelligence Research]''' | '''1076-9757''' | '''11076 - 9757''' | '''3''' | | '''Adnan Darwiche''' |- | colspan="6" | JAIR covers all areas of artificial intelligence (AI), publishing refereed research articles, survey articles, and technical notes. Established in 1993 as one of the first electronic scientific journals, JAIR is indexed by INSPEC, Science Citation Index, and MathSciNet. JAIR reviews papers within approximately three months of submission and publishes accepted articles on the internet immediately upon receiving the final versions. JAIR articles are published for free distribution on the internet by the AI Access Foundation, and for purchase in bound volumes by AAAI Press. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.tandf.co.uk/journals/tf/0952813x.html Journal Of Experimental & Theoretical Artificial Intelligence]''' | '''0952-813X''' | '''1362-3079''' | '''4''' | '''0.500''' | '''Eric Dietrich''' |- | colspan="6" | Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is advancing scientific research in artificial intelligence (AI) by providing a public forum for the presentation, evaluation and criticism of research results, the discussion of methodological issues, and the communication of positions, preliminary findings and research directions. JETAI features work in all subfields of AI research that adopts a scientific rather than engineering methodology, focusing on work in cognitive science, problem-solving, perception, learning, knowledge representation, memory and neural system modelling. All papers are peer-reviewed. |} ===Статистика=== {| class=standard" | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/statistics/statistical+theory+and+methods/journal/357 Journal Of Classification]''' | '''0176-4268''' | '''1432-1343''' | '''2''' | '''0.857''' | '''Willem J. Heiser''' |- | colspan="6" | The Journal of Classification presents original and valuable papers in the field of classification, numerical taxonomy, multidimensional scaling and other ordination techniques, clustering, tree structures and other network models, as well as associated models and algorithms for fitting them. Articles support advances in methodology, while demonstrating compelling substantive applications. The journal also publishes comprehensive review articles. Among the disciplines represented are statistics, psychology, biology, information retrieval, anthropology, archeology, astronomy, business, chemistry, computer science, economics, engineering, geography, geology, linguistics, marketing, mathematics, medicine, political science, psychiatry, sociology, and soil science. Published twice a year, each issue typically comprises four sections: articles, short notes and comments, software abstracts, and book reviews. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.imstat.org/aos/ Annals Of Statistics]''' | '''0090-5364''' | | | | '''Susan Murphy Bernard Silverman''' |- | colspan="6" | The Annals of Statistics aim to publish research papers of highest quality reflecting the many facets of contemporary statistics. Primary emphasis is placed on importance and originality, not on formalism. The journal aims to cover three main areas of statistics, mathematical statistics, applied/interdisciplinary statistics, and computational statistics. Of course many of the best papers will touch on more than one of these general areas, because the discipline of statistics has deep roots in mathematics, and in substantive scientific fields. Mathematical Statistics Mathematics provides the language in which models and the properties of statistical methods are formulated. It is essential for rigor, coherence, clarity and understanding. Consequently, our policy is to continue to play a special role in presenting research at the forefront of mathematical statistics, especially theoretical advances that are likely to have a significant impact on statistical methodology or understanding. Applied and Interdisciplinary Statistics Substantive fields are essential for continued vitality of statistics since they provide the motivation and direction for most of the future developments in statistics. We thus intend to publish papers relating to the role of statistics in interdisciplinary investigations in all fields of natural, medical, technical and social science. Computational Statistics A third force that continues to reshape statistics is the computational revolution, and the Annals will welcome developments in this area. Both in applied and in computational statistics, submissions will be evaluated primarily by the relevance of the issues addressed and the creativity of the proposed solutions. 1. Applications 2. Algorithms 3. Bayesian Methods 4. Causal Inference & Missing Data 5. Computer Intensive Inference 6. Decision Theory 7. Errors in Variables 8. Experimental Design 9. Functional Data Analysis 10. Machine Learning/High Dimensional Data Analysis 11. Graphical Modeling 12. Hypothesis Testing 13. Nonparametric Estimation/Inference 14. Parametric Inference 15. Robust Statistics 16. Semiparametric Inference 17. Sequential Methods 18. Spatial Statistics 19. Survival Analysis 20. Survey Sampling/ Survey Research 21. Stochastic Processes 22. Applied Probability |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/statistics/journal/10463 Annals Of The Institute Of Statistical Mathematics]''' | '''0020-3157''' | '''1572-9052''' | | '''0.38''' | '''G. Kitagawa''' |- | colspan="6" | Annals of the Institute of Statistical Mathematics (AISM) provides an international forum for communication among statisticians and research workers. The journal seeks to advance the field of statistics, enabling people to better manage and cope with uncertainties. It focuses on findings that have the potential to significantly enhance the practice of statistics. AISM features high quality papers across the broad spectrum of statistics. In particular, the journal emphasizes papers that (a) establish new application areas, (b) present new procedures and algorithms, (c) develop unifying theories, (d) analyze and improve existing procedures and theories, and (e) communicate empirical findings supported by real data. In addition to papers by professional statisticians, the journal welcomes contributions from authors in related fields. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.informaworld.com/smpp/title~content=t713597237 Communications In Statistics - Simulation And Computation]''' | '''0361-0918''' | '''1532-4141''' | '''10''' | '''0.207''' | '''N. Balakrishnan''' |- | colspan="6" | The Simulation and Computation series intends to publish papers that make theoretical and methodological advances relating to computational aspects of Probability and Statistics. Simulational assessment and comparison of the performance of statistical and probabilistic methods will also be considered for publication. Papers stressing graphical methods, resampling and other computationally intensive methods will be particularly relevant. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.informaworld.com/smpp/title~content=t713597238 Communications In Statistics - Theory And Methods]''' | '''0361-0926''' | '''1532-415X''' | '''20''' | '''0.240''' | '''N. Balakrishnan''' |- | colspan="6" | The Theory and Methods series intends to publish papers that make theoretical and methodological advances in Probability and Statistics. New applications of statistical and probabilistic methods will also be considered for publication. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/statistics/journal/180?detailspage=aimsandscopes Computational Statistics] ''' | '''0943-4062''' | '''1613-9658''' | | | '''Friedrich Leisch''' |- | colspan="6" | Computational Statistics (CompStat) is an international journal which promotes the publication of applications and methodological research in the field of Computational Statistics. The focus of papers in CompStat is on the contribution to and influence of computing on statistics and vice versa. The journal provides a forum for computer scientists, mathematicians, and statisticians in a variety of fields of statistics such as biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge based systems, and Bayesian computing. CompStat publishes hardware, software plus package reports as well as book reviews. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/locate/csda Computational Statistics & Data Analysis]''' | '''0167-9473''' | | '''12''' | '''1.029''' | '''S.P. Azen''' |- | colspan="6" | The Official Journal of the International Association for Statistical Computing Computational Statistics& Data Analysis, the official journal of the International Association of Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, divided ... click here for full Aims & Scope Computational Statistics& Data Analysis, the official journal of the International Association of Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, divided into thefollowing subject areas: I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., bioinformatics, computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, neural networks, numerical methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. II) Statistical Methodology for Data Analysis - Manuscripts dealing with data analysis strategies and methodologies (e.g., biostatistics, classification, clinical trial methodology, data exploration, density estimation, design of experiments, model free data exploration, pattern recognition/image analysis, robust procedures, statistical genetics). III) Special Applications - Manuscripts at the interface of statistics and computers (e.g., comparison of statistical methodology, computer-assisted instruction for statistics, simulation experiments). |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.informaworld.com/smpp/title~content=t713428038 Journal Of Applied Statistics]''' | '''0266-4763''' | '''1360-0532''' | '''12''' | '''0.222''' | '''Robert G. Aykroyd''' |- | colspan="6" | Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees. Each issue aims for a balance of methodological innovation, thorough evaluation of existing techniques, case studies, speculative articles, book reviews and letters. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://pubs.amstat.org/loi/jcgs Journal Of Computational And Graphical Statistics]''' | '''1061-8600''' | | '''4''' | | '''David van Dyk''' |- | colspan="6" | JCGS presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.tandf.co.uk/journals/journal.asp?issn=1048-5252&subcategory=mm400000 Journal Of Nonparametric Statistics]''' | '''1048-5252''' | '''1029-0311''' | '''8''' | '''0.406''' | '''Suojin Wang''' |- | colspan="6" | Journal of Nonparametric Statistics provides a medium for the publication of research and survey work in nonparametric statistics and related areas. The scope includes, but is not limited to the following topics: * Nonparametric modeling * Nonparametric function estimation * Rank and other robust and distribution-free procedures * Resampling methods * Lack-of-fit testing * Multivariate analysis * Inference with high-dimensional data * Dimension reduction and variable selection * Methods for errors in variables, missing, censored, and other incomplete data structures * Inference of stochastic processes * Sample surveys * Time series analysis * Longitudinal and functional data analysis * Nonparametric Bayes methods and decision procedures * Semiparametric models and procedures * Statistical methods for imaging and tomography * Statistical inverse problems * Financial statistics and econometrics * Bioinformatics and comparative genomics * Statistical algorithms and machine learning. Both the theory and applications of nonparametric statistics are covered in the journal. Research applying nonparametric methods to medicine, engineering, technology, science and humanities is welcomed, provided the novelty and quality level are of the highest order. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.tandf.co.uk/journals/titles/00949655.asp Journal Of Statistical Computation And Simulation]''' | '''0094-9655''' | '''1563-5163''' | '''12''' | '''0.387''' | '''Richard Krutchkoff''' |- | colspan="6" | Journal of Statistical Computation and Simulation publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/505561/description#description Journal Of Statistical Planning And Inference]''' | '''0378-3758''' | | '''12''' | '''0.559''' | '''N. Balakrishnan''' |- | colspan="6" | This is a broad based journal covering all branches of statistics, with special encouragement to workers in the field of statistical planning and related combinatorial mathematics and probability theory. We look upon Planning and Inference as the two twin branches of statistics, the former being concerned with how to collect data (or information) appropriately, and the latter with how to analyze or summarise the information after it has been collected. The data may be collected in one or more attempts, or one or more variables, and may be subject to relatively simple or more complex stochastic processes. Thus, the major areas, such as experimental design (single- or multi-stage or sequential), sampling, certain branches of information theory, multivariate analysis, decision theory, distribution free methods, data analysis, probabilistic modelling, reliability, etc. are all included. A large variety of statistical problems, particularly those in statistical planning, necessarily involve combinatorial or discrete mathematics. One main feature of this journal is that it particularly encourages papers in all branches of combinatorial mathematics which have some bearing on statistical problems. The journal encourages papers on the application of Statistics to scientific problems. It welcomes research papers, survey articles, book reviews, and material for the Statistical Discussion Forum. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.tandf.co.uk/journals/titles/02331888.asp Statistics]''' | '''0233-1888''' | '''1029-4910''' | '''6''' | '''0.289''' | '''O. Bunke''' |- | colspan="6" | Statistics publishes theoretical and applied papers related to the different fields of statistics such as regression and variance analysis, design of experiments, foundations of statistical inference, statistical decision theory, testing hypotheses, parameter estimation, nonparametric methods, sequential procedures, time series and statistical problems for stochastic processes, and statistical data analysis. It is expected that the papers give interesting and novel contributions to statistical theory and its applications at a good mathematical level. The results should be presented in form of theorems together with their mathematical proofs, which should not be merely routine calculations. Additionally, the discussion of results and their value for the theory or for applications could be a valuable addition, as well as numerical results on the efficiency or examples for the application of the theoretical results. A special section is devoted to survey papers on theory and methods in interesting areas of statistics. The Journal may also publish proceedings of conferences and announcements on related topics. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.elsevier.com/wps/find/journaldescription.cws_home/505573/description#description Statistics & Probability Letters]''' | '''0167-7152''' | | '''24''' | '''0.328''' | '''S. Datta H. Koul''' |- | colspan="6" | STATISTICS & PROBABILITY LETTERS adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature. All areas of statistics and probability, including biostatistics and statistical bioinformatics, will be covered extensively. STATISTICS & PROBABILITY LETTERS is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in STATISTICS & PROBABILITY LETTERS. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission. The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of STATISTICS & PROBABILITY LETTERS is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability. The mainstream of LETTERS will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines, especially biostatistics and bioinformatics. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published. We also plan to publish applications and case studies that demonstrate a novel use of existing techniques or have interesting innovative ideas about data collection, modelling or inference. |- | Название | ISSN печ. | ISSN эл. | Вып. в год | Impact | Главный редактор |- class="dark" | '''[http://www.springer.com/statistics/computational/journal/11222 Statistics And Computing]''' | '''0960-3174''' | '''1573-1375''' | | '''1.136''' | '''Gilles Celeux''' |- | colspan="6" | Statistics and Computing is a quarterly refereed journal that publishes papers exploring the interface between statistics and computer science. In particular, the journal addresses the use of statistical concepts in computer science and the use of computers in data analysis. A partial list of topics includes techniques for evaluating analytically intractable problems, search and optimization methods, computer-intensive (resampling) methods, simulation and Monte Carlo, graphics, computer environments, reliability of hardware, statistical approaches to software errors, information retrieval, and statistics of databases. In addition to original research reports, the journal publishes authoritative topical reviews, discussions about papers, and book and software reviews. Periodically, special issues are published that are dedicated to important and emerging topics or the proceedings of relevant conferences. |} === См. также === * [http://www.periodicals.com/ www.periodicals.com] * [http://www.journalseek.net/ www.journalseek.net] [[Категория:Рекомендации для студентов]]

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