Novel Developments In Granular Computing Applications For Advanced Human Reasoning And Soft Computation

Author: Yao, JingTao
Editor: IGI Global
ISBN: 1605663255
File Size: 77,57 MB
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"This book investigages granular computing (GrC), which emerged as one of the fastest growing information processing paradigms in computational intelligence and human-centric systems"--Provided by publisher.

Granular Computing And Intelligent Systems

Author: Witold Pedrycz
Editor: Springer Science & Business Media
ISBN: 9783642198205
File Size: 34,34 MB
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Information granules are fundamental conceptual entities facilitating perception of complex phenomena and contributing to the enhancement of human centricity in intelligent systems. The formal frameworks of information granules and information granulation comprise fuzzy sets, interval analysis, probability, rough sets, and shadowed sets, to name only a few representatives. Among current developments of Granular Computing, interesting options concern information granules of higher order and of higher type. The higher order information granularity is concerned with an effective formation of information granules over the space being originally constructed by information granules of lower order. This construct is directly associated with the concept of hierarchy of systems composed of successive processing layers characterized by the increasing levels of abstraction. This idea of layered, hierarchical realization of models of complex systems has gained a significant level of visibility in fuzzy modeling with the well-established concept of hierarchical fuzzy models where one strives to achieve a sound tradeoff between accuracy and a level of detail captured by the model and its level of interpretability. Higher type information granules emerge when the information granules themselves cannot be fully characterized in a purely numerical fashion but instead it becomes convenient to exploit their realization in the form of other types of information granules such as type-2 fuzzy sets, interval-valued fuzzy sets, or probabilistic fuzzy sets. Higher order and higher type of information granules constitute the focus of the studies on Granular Computing presented in this study. The book elaborates on sound methodologies of Granular Computing, algorithmic pursuits and an array of diverse applications and case studies in environmental studies, option price forecasting, and power engineering.

Interpretable Artificial Intelligence A Perspective Of Granular Computing

Author: Witold Pedrycz
Editor: Springer Nature
ISBN: 3030649490
File Size: 21,82 MB
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Developments In Natural Intelligence Research And Knowledge Engineering Advancing Applications

Author: Wang, Yingxu
Editor: IGI Global
ISBN: 1466617446
File Size: 80,53 MB
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"This book covers the intricate worlds of thought, comprehension, intelligence, and knowledge through the scientific field of Cognitive Science, covering topics that have been pivotal at major conferences covering Cognitive Science"--Provided by publisher.

Advances In Machine Learning Ii

Author: Jacek Koronacki
Editor: Springer Science & Business Media
ISBN: 3642051782
File Size: 34,98 MB
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This is the second volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area in modern computer science and information technology. His research career started in the mid-1960s in Poland, in the Institute of Automation, Polish Academy of Sciences in Warsaw, Poland. He left for the USA in 1970, and since then had worked there at various universities, notably, at the University of Illinois at Urbana – Champaign and finally, until his untimely death, at George Mason University. We, the editors, had been lucky to be able to meet and collaborate with Ryszard for years, indeed some of us knew him when he was still in Poland. After he started working in the USA, he was a frequent visitor to Poland, taking part at many conferences until his death. We had also witnessed with a great personal pleasure honors and awards he had received over the years, notably when some years ago he was elected Foreign Member of the Polish Academy of Sciences among some top scientists and scholars from all over the world, including Nobel prize winners. Professor Michalski’s research results influenced very strongly the development of machine learning, data mining, and related areas. Also, he inspired many established and younger scholars and scientists all over the world. We feel very happy that so many top scientists from all over the world agreed to pay the last tribute to Professor Michalski by writing papers in their areas of research. These papers will constitute the most appropriate tribute to Professor Michalski, a devoted scholar and researcher. Moreover, we believe that they will inspire many newcomers and younger researchers in the area of broadly perceived machine learning, data analysis and data mining. The papers included in the two volumes, Machine Learning I and Machine Learning II, cover diverse topics, and various aspects of the fields involved. For convenience of the potential readers, we will now briefly summarize the contents of the particular chapters.

Rough Sets Fuzzy Sets Data Mining And Granular Computing

Author: Yiyu Yao
Editor: Springer
ISBN: 3319257838
File Size: 53,12 MB
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This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2015, held in Tianjin, China in November 2015 as one of the co-located conference of the 2015 Joint Rough Set Symposium, JRS 2015. The 44 papers were carefully reviewed and selected from 97 submissions. The papers in this volume cover topics such as rough sets: the experts speak; generalized rough sets; rough sets and graphs; rough and fuzzy hybridization; granular computing; data mining and machine learning; three-way decisions; IJCRS 2015 data challenge.

Computer Engineering Concepts Methodologies Tools And Applications

Author: Management Association, Information Resources
Editor: IGI Global
ISBN: 1613504578
File Size: 74,72 MB
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"This reference is a broad, multi-volume collection of the best recent works published under the umbrella of computer engineering, including perspectives on the fundamental aspects, tools and technologies, methods and design, applications, managerial impact, social/behavioral perspectives, critical issues, and emerging trends in the field"--Provided by publisher.

Human Centric Information Processing Through Granular Modelling

Author: Andrzej Bargiela
Editor: Springer Science & Business Media
ISBN: 3540929150
File Size: 79,51 MB
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Information granules and their processing permeate a way in which we perceive the world, carryout processing at the conceptual (abstract) level, and communicate our findings to the surrounding environment. The importance of information granulation becomes even more apparent when we are faced with a rapidly growing flood of data, become challenged to make decisions in complex data settings and are required to appreciate the context from which the data is derived. Human centricity of systems that claim to be “intelligent” and the granular computing come hand in hand. It is not surprising at all to witness that the paradigm of Granular Computing has started to gain visibility and continues along this path by gathering interest from the circles of academics and practitioners. It is quite remarkable that the spectrum of application and research areas that have adopted information granulation as a successful strategy for dealing with information complexity covers such diverse fields as bioinformatics, image understanding, environmental monitoring, urban sustainability, to mention few most visible in the literature. Undoubtedly, there are two important aspects of Granular Computing that are worth stressing. First, there are several formalisms in which information granules are articulated so be intervals (sets), fuzzy sets, rough sets, soft sets, approximate sets, near sets and alike. They are complementary and each of them offers some interesting views at the complexity of the world and cyberspace.

Rough Sets

Author: Lech Polkowski
Editor: Springer
ISBN: 3319608371
File Size: 70,23 MB
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This two-volume set LNAI 10313 and LNAI 10314 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2017, held in Olsztyn, Poland, in July 2017. The 74 revised full papers presented together with 16 short papers and 16 invited talks, were carefully reviewed and selected from 130 submissions. The papers in this two set-volume of IJCRS 2017 follow the track already rutted by RSCTC and JRS conferences which aimed at unification of many facets of rough set theory from theoretical aspects of the rough set idea bordering on theory of concepts and going through algebraic structures, topological structures, logics for uncertain reasoning, decision algorithms, relations to other theories of vagueness and ambiguity, then to extensions of the rough set idea like granular structures, rough mereology, and to applications of the idea in diverse fields of applied science including hybrid methods like rough-fuzzy, neuro-rough, neuro-rough-fuzzy computing. IJCRS 2017 encompasses topics spread among four main tracks: Rough Sets and Data Science (in relation to RSCTC series organized since 1998); Rough Sets and Granular Computing (in relation to RSFDGrC series organized since 1999); Rough Sets and Knowledge Technology (in relation to RSKT series organized since 2006); and Rough Sets and Intelligent Systems (in relation to RSEISP series organized since 2007).

Springer Handbook Of Computational Intelligence

Author: Janusz Kacprzyk
Editor: Springer
ISBN: 3662435055
File Size: 59,85 MB
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The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Ai 2018 Advances In Artificial Intelligence

Author: Tanja Mitrovic
Editor: Springer
ISBN: 3030039919
File Size: 72,82 MB
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This book constitutes the proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, AI 2018, held in Wellington, New Zealand, in December 2018. The 50 full and 26 short papers presented in this volume were carefully reviewed and selected from 125 submissions. The paper were organized in topical sections named: agents, games and robotics; AI applications and innovations; computer vision; constraints and search; evolutionary computation; knowledge representation and reasoning; machine learning and data mining; planning and scheduling; and text mining and NLP.

Learning In Non Stationary Environments

Author: Moamar Sayed-Mouchaweh
Editor: Springer Science & Business Media
ISBN: 1441980202
File Size: 29,88 MB
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Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy. Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations. This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research.

Rough Sets And Knowledge Technology

Author: Pawan Lingras
Editor: Springer
ISBN: 3642412998
File Size: 29,55 MB
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This book constitutes the thoroughly refereed conference proceedings of the 8th International Conference on Rough Sets and Knowledge Technology, RSKT 2013, held in Halifax, Canada in October 2013 as one of the co-located conferences of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as history and future of rough sets; foundations and probabilistic rough sets; rules, reducts, ensembles; new trends in computing; three-way decision rough sets; and learning, predicting, modeling.

Rough Sets And Knowledge Technology

Author: Peng Wen
Editor: Springer Science & Business Media
ISBN: 3642029612
File Size: 18,93 MB
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The Rough Sets and Knowledge Technology (RSKT) conferences serve as a - jor forum that brings researchers and industry practitioners together to discuss and deliberate on fundamental issues of knowledge processing and management and knowledge-intensive practical solutions in the current knowledge age. - perts from around the world meet annually to present state-of-the-art sci- ti?c results, to nurture academic and industrial interaction, and to promote collaborative research in rough sets and knowledge technology. The main theme of the RSKT conference is to explore the synergy between rough sets and - vanced knowledge technology and applications, including knowledge discovery, datamining,knowledgeprocessingandmanagement,granularcomputing,evo- tionary computing, biocomputing and bioinformatics, cognitive computing and cognitive informatics, natural and arti?cial intelligence, Web intelligence, c- plex systems, and many others. The ?rst RSKT conference was held in 2006 in Chongqing, P.R. China, f- lowed by RSKT 2007 in Toronto, Canada and RSKT 2008 in Chengdu, P.R. China. This volume contains the papers selected for presentation at the 4th - ternationalConferenceonRoughSetsandKnowledgeTechnology(RSKT2009), which was held during July 14-16 on the Gold Coast, Australia.

Computer Information Systems And Industrial Management

Author: Khalid Saeed
Editor: Springer
ISBN: 3319453785
File Size: 35,12 MB
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This book constitutes the proceedings of the 15th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2016, held in Vilnius, Lithuania, in September 2016. The 63 regular papers presented together with 1 inivted paper and 5 keynotes in this volume were carefully reviewed and selected from about 89 submissions. The main topics covered are rough set methods for big data analytics; images, visualization, classification; optimization, tuning; scheduling in manufacturing and other applications; algorithms; decisions; intelligent distributed systems; and biometrics, identification, security.

Brain Informatics

Author: Ning Zhong
Editor: Springer
ISBN: 3642049540
File Size: 10,14 MB
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This volume contains the papers selected for presentation at The 2009 Inter- tional Conference on Brain Informatics (BI 2009) held at Beijing University of Technology, China, on October 22–24, 2009. It was organized by the Web Int- ligence Consortium (WIC) and IEEE Computational Intelligence Society Task Force on Brain Informatics (IEEE TF-BI). The conference was held jointly with The 2009 International Conference on Active Media Technology (AMT 2009). Brain informatics (BI) has emergedas an interdisciplinaryresearch?eld that focuses on studying the mechanisms underlying the human information proce- ing system (HIPS). It investigates the essential functions of the brain, ranging from perception to thinking, and encompassing such areas as multi-perception, attention,memory,language,computation,heuristicsearch,reasoning,planning, decision-making, problem-solving, learning, discovery, and creativity. The goal of BI is to develop and demonstrate a systematic approach to achieving an integrated understanding of both macroscopic and microscopic level working principles of the brain, by means of experimental, computational, and cognitive neuroscience studies, as well as utilizing advanced Web Intelligence (WI) centric information technologies. BI represents a potentially revolutionary shift in the way that research is undertaken. It attempts to capture new forms of c- laborative and interdisciplinary work. Following this vision, new kinds of BI methods and global research communities will emerge, through infrastructure on the wisdom Web and knowledge grids that enables high speed and d- tributed, large-scale analysis and computations, and radically new ways of sh- ing data/knowledge.

Agent And Multi Agent Systems Technologies And Applications

Author: Piotr Jedrzejowicz
Editor: Springer Science & Business Media
ISBN: 3642134793
File Size: 38,76 MB
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The LNAI series reports state-of-the-art results in artificial intelligence research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelligent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes -proceedings (published in time for the respective conference) -post-proceedings (consisting of thoroughly revised final full papers) -research monographs (which may be based on PhD work) More recently, several color-cover sublines have been added featuring, beyond a collection of papers, various added-value components; these sublines include -tutorials (textbook-like monographs or collections of lectures given at advanced courses) -state-of-the-art surveys (offering complete and mediated coverage of a topic) -hot topics (introducing emergent topics to the broader community)

Rough Sets And Knowledge Technology

Author: Tianrui Li
Editor: Springer
ISBN: 3642319009
File Size: 75,18 MB
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This book constitutes the refereed proceedings of the 7th International Conference on Rough Sets and Knowledge Technology, RSKT 2012, held in Chengdu, China during August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 63 revised papers (including 42 regular and 21 short papers) were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets and its generalizations, rough sets in data and knowledge processing, knowledge technology, advances in granular computing (AGC 2012 workshop), decision-theoretic rough set model and applications (special session), intelligent decision making and granular computing (special session), rough set foundations (special session).

Pattern Recognition And Machine Intelligence

Author: Santanu Chaudhury
Editor: Springer Science & Business Media
ISBN: 3642111637
File Size: 23,17 MB
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This book constitutes the refereed proceedings of the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009, held in New Delhi, India in December 2009. The 98 revised papers presented were carefully reviewed and selected from 221 initial submissions. The papers are organized in topical sections on pattern recognition and machine learning, soft computing andapplications, bio and chemo informatics, text and data mining, image analysis, document image processing, watermarking and steganography, biometrics, image and video retrieval, speech and audio processing, as well as on applications.

Pattern Recognition And Big Data

Author: Pal Sankar Kumar
Editor: World Scientific
ISBN: 9813144564
File Size: 58,78 MB
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Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications. Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.