Fundamentals of computational intelligence : (Record no. 42623)

000 -LEADER
fixed length control field 09166nam a2201453 i 4500
001 - CONTROL NUMBER
control field 7547467
003 - CONTROL NUMBER IDENTIFIER
control field IEEE
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20191218152127.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr |n|||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160920s2008 nju ob 001 eng d
019 ## -
-- 954045921
-- 957615443
-- 958350488
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1119214408
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119214403
Qualifying information electronic
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119214342
Qualifying information print
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119214359
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 1119214351
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119214366
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 111921436X
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119214403
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 1119214343
035 ## - SYSTEM CONTROL NUMBER
System control number (CaBNVSL)mat07547467
035 ## - SYSTEM CONTROL NUMBER
System control number (IDAMS)0b00006485691f5c
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.76.E95
Item number K45 2016eb
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.33
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Keller, James M.,
Relator term author.
245 10 - TITLE STATEMENT
Title Fundamentals of computational intelligence :
Remainder of title neural networks, fuzzy systems, and evolutionary computation /
Statement of responsibility, etc. James M. Keller, Derong Liu, David B. Fogel.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Hoboken, New Jersey :
Name of producer, publisher, distributor, manufacturer IEEE Press/Wiley,
Date of production, publication, distribution, manufacture, or copyright notice 2016.
264 #2 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture [Piscataqay, New Jersey] :
Name of producer, publisher, distributor, manufacturer IEEE Xplore,
Date of production, publication, distribution, manufacture, or copyright notice [2016]
300 ## - PHYSICAL DESCRIPTION
Extent 1 PDF (400 pages).
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term electronic
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement IEEE Press series on computational intelligence
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 6: Basic Fuzzy Set Theory6.1 Introduction; 6.2 A Brief History; 6.3 Fuzzy Membership Functions and Operators; 6.3.1 Membership Functions; 6.3.2 Basic Fuzzy Set Operators; 6.4 Alpha-Cuts, the Decomposition Theorem, and the Extension Principle; 6.5 Compensatory Operators; 6.6 Conclusions; Exercises; Chapter 7: Fuzzy Relations and Fuzzy Logic Inference; 7.1 Introduction; 7.2 Fuzzy Relations and Propositions; 7.3 Fuzzy Logic Inference; 7.4 Fuzzy Logic for Real-Valued Inputs; 7.5 Where Do the Rules Come From?; 7.6 Chapter Summary; Exercises; Chapter 8: Fuzzy Clustering and Classification
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation; Table of Contents; Acknowledgments; Chapter 1: Introduction to Computational Intelligence; 1.1 Welcome to Computational Intelligence; 1.2 What Makes This Book Special; 1.3 What This Book Covers; 1.4 How to Use This Book; 1.5 Final Thoughts Before You Get Started; Part I: Neural Networks; Chapter 2: Introduction and Single-Layer Neural Networks; 2.1 Short History of Neural Networks; 2.2 Rosenblatt's Neuron; 2.3 Perceptron Training Algorithm; 2.3.1 Test Problem
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2.3.2 Constructing Learning Rules2.3.3 Unified Learning Rule; 2.3.4 Training Multiple-Neuron Perceptrons; 2.3.4.1 Problem Statement; 2.4 The Perceptron Convergence Theorem; 2.5 Computer Experiment Using Perceptrons; 2.6 Activation Functions; 2.6.1 Threshold Function; 2.6.2 Sigmoid Function; Exercises; Chapter 3: Multilayer Neural Networks and Backpropagation; 3.1 Universal Approximation Theory; 3.2 The Backpropagation Training Algorithm; 3.2.1 The Description of the Algorithm; 3.2.2 The Strategy for Improving the Algorithm; 3.2.3 The Design Procedure of the Algorithm
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3.3 Batch Learning and Online Learning3.3.1 Batch Learning; 3.3.2 Online Learning; 3.4 Cross-Validation and Generalization; 3.4.1 Cross-Validation; 3.4.2 Generalization; 3.4.3 Convolutional Neural Networks; 3.5 Computer Experiment Using Backpropagation; Exercises; Chapter 4: Radial-Basis Function Networks; 4.1 Radial-Basis Functions; 4.2 The Interpolation Problem; 4.3 Training Algorithms for Radial-Basis Function Networks; 4.3.1 Layered Structure of a Radial-Basis Function Network; 4.3.2 Modification of the Structure of RBF Network; 4.3.3 Hybrid Learning Process; 4.4 Universal Approximation
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4.5 Kernel RegressionExercises; Chapter 5: Recurrent Neural Networks; 5.1 The Hopfield Network; 5.2 The Grossberg Network; 5.2.1 Basic Nonlinear Model; 5.2.2 Two-Layer Competitive Network; 5.2.2.1 Layer 1; 5.2.2.2 Layer 2; 5.2.2.3 Learning Law; Basic Nonlinear Model: Leaky Integrator; Layer 1; Layer 2; 5.3 Cellular Neural Networks; 5.4 Neurodynamics and Optimization; 5.5 Stability Analysis of Recurrent Neural Networks; 5.5.1 Stability Analysis of the Hopfield Network; 5.5.2 Stability Analysis of the Cohen-Grossberg Network; Exercises; Part II: Fuzzy Set Theory and Fuzzy Logic
506 1# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Restricted to subscribers or individual electronic text purchasers.
520 ## - SUMMARY, ETC.
Summary, etc. Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. . Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks. Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals. Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence. Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print.
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Online resource; title from PDF title page (EBSCO, viewed August 12, 2016)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Expert systems (Computer science)
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Expert systems (Computer science)
Source of heading or term fast
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
695 ## -
-- Airports
695 ## -
-- Axons
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-- Backpropagation
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-- Backpropagation algorithms
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-- Biological neural networks
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-- Biological system modeling
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-- Birds
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-- Brain modeling
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-- Classification algorithms
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-- Clustering algorithms
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-- Complexity theory
695 ## -
-- Computational modeling
695 ## -
-- Computers
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-- Correlation
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-- Data models
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-- Data visualization
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-- Decision making
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-- Delay effects
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-- Density measurement
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-- Design methodology
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-- Evolution (biology)
695 ## -
-- Evolutionary computation
695 ## -
-- Explosives
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-- Extraterrestrial measurements
695 ## -
-- Foot
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-- Fuzzy logic
695 ## -
-- Fuzzy set theory
695 ## -
-- Fuzzy sets
695 ## -
-- Fuzzy systems
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-- Genetics
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-- Hair
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-- History
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-- Hopfield neural networks
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-- Image recognition
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-- Interpolation
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-- Linear programming
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-- Mathematical model
695 ## -
-- Measurement
695 ## -
-- Measurement uncertainty
695 ## -
-- Medical services
695 ## -
-- Multilayer perceptrons
695 ## -
-- Neural networks
695 ## -
-- Neurons
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-- Nonhomogeneous media
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-- Optimization
695 ## -
-- Organisms
695 ## -
-- Particle swarm optimization
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-- Pattern recognition
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-- Phase change materials
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-- Pragmatics
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-- Predictive models
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-- Problem-solving
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-- Radial basis function networks
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-- Random variables
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-- Search problems
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-- Sociology
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-- Standards
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-- Statistics
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-- Surface contamination
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-- Surface morphology
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-- Surface treatment
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-- Training
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-- Training data
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-- Uncertainty
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-- Unsupervised learning
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-- Urban areas
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-- Vegetation
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Liu, Derong,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Fogel, David B.,
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element IEEE Xplore (Online Service),
Relator term distributor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Wiley,
Relator term publisher.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Main entry heading Keller, James M.
Title Fundamentals of Computational Intelligence : Neural Networks, Fuzzy Systems, and Evolutionary Computation
Place, publisher, and date of publication Hoboken : Wiley,c2016
International Standard Book Number 9781119214403
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title IEEE series on computational intelligence.
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to resource
Uniform Resource Identifier https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7547467

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