LEADER 05529nam 22006615 450 001 996464539003316 005 20230810170518.0 010 $a3-030-42227-5 024 7 $a10.1007/978-3-030-42227-1 035 $a(MiAaPQ)EBC6940156 035 $a(Au-PeEL)EBL6940156 035 $a(CKB)21428049300041 035 $a(DE-He213)978-3-030-42227-1 035 $a(PPN)261518801 035 $a(EXLCZ)9921428049300041 100 $a20220326d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Intelligence$b[electronic resource] $eA Methodological Introduction /$fby Rudolf Kruse, Sanaz Mostaghim, Christian Borgelt, Christian Braune, Matthias Steinbrecher 205 $a3rd ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (629 pages) 225 1 $aTexts in Computer Science,$x1868-095X 300 $aIncludes index. 311 08$aPrint version: Kruse, Rudolf Computational Intelligence Cham : Springer International Publishing AG,c2022 9783030422264 327 $aIntroduction -- Part I: Neural Networks -- Introduction -- Threshold Logic Units -- General Neural Networks -- Multi-Layer Perceptrons -- Radial Basis Function Networks -- Self-Organizing Maps -- Hopfield Networks -- Recurrent Networks -- Mathematical Remarks for Neural Networks -- Part II: Evolutionary Algorithms -- Introduction to Evolutionary Algorithms -- Elements of Evolutionary Algorithms -- Fundamental Evolutionary Algorithms -- Computational Swarm Intelligence -- Part III: Fuzzy Systems -- Fuzzy Sets and Fuzzy Logic -- The Extension Principle -- Fuzzy Relations -- Similarity Relations -- Fuzzy Control -- Fuzzy Data Analysis -- Part IV: Bayes and Markov Networks -- Introduction to Bayes Networks -- Elements of Probability and Graph Theory -- Decompositions -- Evidence Propagation -- Learning Graphical Models -- Belief Revision -- Decision Graphs. 330 $aComputational intelligence comprises concepts, paradigms, algorithms, and implementations of systems that are intended to exhibit intelligent behavior in complex environments. It relies heavily on (at least) nature-inspired methods, which have the advantage that they tolerate incomplete, imprecise and uncertain knowledge and thus also facilitate finding solutions that are approximative, manageable and robust at the same time. Fully updated, this new edition of the authoritative textbook provides a clear and logical introduction to Computational Intelligence, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. Rather than aim for completeness, the goal is to give a methodical introduction, supporting fundamental concepts and their implementations with explanation of the theoretical background of proposed problem solutions. Topics and features: Offers new material on deep learning, scalarization, large-scale optimization algorithms, and collective decision-making algorithms Contains numerous classroom-tested examples and definitions Discusses in detail the classical areas of artificial neural networks, fuzzy systems, evolutionary algorithms, and Bayes and Markov networks Reviews the latest developments, including such topics as ant colony optimization and probabilistic graphical models Provides supplementary material, including module descriptions, lecture slides, exercises with solutions, and software tools This seminal textbook is primarily meant as a companion book for lectures on the covered topics in the area of computational intelligence. However, it is also eminently suitable as a guidebook for self-study by students and practitioners from industry and commerce. Dr. Rudolf Kruse is the former leader of the Computational Intelligence Research Group and now Emeritus Professor of the Department of Computer Science at the University of Magdeburg, Germany. Dr. Sanaz Mostaghim is a full Professor of Computer Science and Dr. Christian Braune is a Senior Lecturer at the same institution. Dr. Christian Borgelt is a Professor of Data Science at the Paris Lodron University of Salzburg, Austria. Dr. Matthias Steinbrecher is a Development Architect at SAP SE, Potsdam, Germany. 410 0$aTexts in Computer Science,$x1868-095X 606 $aArtificial intelligence 606 $aEngineering mathematics 606 $aEngineering$xData processing 606 $aComputational intelligence 606 $aComputer science 606 $aArtificial Intelligence 606 $aMathematical and Computational Engineering Applications 606 $aComputational Intelligence 606 $aTheory and Algorithms for Application Domains 615 0$aArtificial intelligence. 615 0$aEngineering mathematics. 615 0$aEngineering$xData processing. 615 0$aComputational intelligence. 615 0$aComputer science. 615 14$aArtificial Intelligence. 615 24$aMathematical and Computational Engineering Applications. 615 24$aComputational Intelligence. 615 24$aTheory and Algorithms for Application Domains. 676 $a006.3 700 $aKruse$b Rudolf$0102093 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464539003316 996 $aComputational Intelligence$92111553 997 $aUNISA