{"product_id":"fundamentals-of-computational-intelligence-9781119214342","title":"Fundamentals of Computational Intelligence","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eProvides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDiscusses single-layer and multilayer neural networks, radial-basis functi\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eAcknowledgments xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1. Introduction to Computational Intelligence 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Welcome to Computational Intelligence 1\u003c\/p\u003e \u003cp\u003e1.2 What Makes This Book Special 1\u003c\/p\u003e \u003cp\u003e1.3 What This Book Covers 2\u003c\/p\u003e \u003cp\u003e1.4 How to Use This Book 2\u003c\/p\u003e \u003cp\u003e1.5 Final Thoughts Before You Get Started 3\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I NEURAL NETWORKS 5\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. Introduction and Single-Layer Neural Networks 7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Short History of Neural Networks 9\u003c\/p\u003e \u003cp\u003e2.2 Rosenblatt’s Neuron 10\u003c\/p\u003e \u003cp\u003e2.3 Perceptron Training Algorithm 13\u003c\/p\u003e \u003cp\u003e2.4 The Perceptron Convergence Theorem 23\u003c\/p\u003e \u003cp\u003e2.5 Computer Experiment Using Perceptrons 25\u003c\/p\u003e \u003cp\u003e2.6 Activation Functions 28\u003c\/p\u003e \u003cp\u003eExercises 30\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. Multilayer Neural Networks and Backpropagation 35\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Universal Approximation Theory 35\u003c\/p\u003e \u003cp\u003e3.2 The Backpropagation Training Algorithm 37\u003c\/p\u003e \u003cp\u003e3.3 Batch Learning and Online Learning 45\u003c\/p\u003e \u003cp\u003e3.4 Cross-Validation and Generalization 47\u003c\/p\u003e \u003cp\u003e3.5 Computer Experiment Using Backpropagation 53\u003c\/p\u003e \u003cp\u003eExercises 56\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4. Radial-Basis Function Networks 61\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Radial-Basis Functions 61\u003c\/p\u003e \u003cp\u003e4.2 The Interpolation Problem 62\u003c\/p\u003e \u003cp\u003e4.3 Training Algorithms For Radial-Basis Function Networks 64\u003c\/p\u003e \u003cp\u003e4.4 Universal Approximation 69\u003c\/p\u003e \u003cp\u003e4.5 Kernel Regression 70\u003c\/p\u003e \u003cp\u003eExercises 75\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. Recurrent Neural Networks 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 The Hopfield Network 77\u003c\/p\u003e \u003cp\u003e5.2 The Grossberg Network 81\u003c\/p\u003e \u003cp\u003e5.3 Cellular Neural Networks 88\u003c\/p\u003e \u003cp\u003e5.4 Neurodynamics and Optimization 91\u003c\/p\u003e \u003cp\u003e5.5 Stability Analysis of Recurrent Neural Networks 93\u003c\/p\u003e \u003cp\u003eExercises 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II FUZZY SET THEORY AND FUZZY LOGIC 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Basic Fuzzy Set Theory 103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 103\u003c\/p\u003e \u003cp\u003e6.2 A Brief History 107\u003c\/p\u003e \u003cp\u003e6.3 Fuzzy Membership Functions and Operators 108\u003c\/p\u003e \u003cp\u003e6.4 Alpha-Cuts, The Decomposition Theorem, and The Extension Principle 117\u003c\/p\u003e \u003cp\u003e6.5 Compensatory Operators 120\u003c\/p\u003e \u003cp\u003e6.6 Conclusions 124\u003c\/p\u003e \u003cp\u003eExercises 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Fuzzy Relations and Fuzzy Logic Inference 127\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 127\u003c\/p\u003e \u003cp\u003e7.2 Fuzzy Relations and Propositions 128\u003c\/p\u003e \u003cp\u003e7.3 Fuzzy Logic Inference 131\u003c\/p\u003e \u003cp\u003e7.4 Fuzzy Logic For Real-Valued Inputs 135\u003c\/p\u003e \u003cp\u003e7.5 Where Do The Rules Come From? 138\u003c\/p\u003e \u003cp\u003e7.6 Chapter Summary 142\u003c\/p\u003e \u003cp\u003eExercises 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. Fuzzy Clustering and Classification 147\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction to Fuzzy Clustering 147\u003c\/p\u003e \u003cp\u003e8.2 Fuzzy c-Means 155\u003c\/p\u003e \u003cp\u003e8.3 An Extension of The Fuzzy c-Means 167\u003c\/p\u003e \u003cp\u003e8.4 Possibilistic c-Means 169\u003c\/p\u003e \u003cp\u003e8.5 Fuzzy Classifiers: Fuzzy k-Nearest Neighbors 174\u003c\/p\u003e \u003cp\u003e8.6 Chapter Summary 179\u003c\/p\u003e \u003cp\u003eExercises 180\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. Fuzzy Measures and Fuzzy Integrals 183\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Fuzzy Measures 183\u003c\/p\u003e \u003cp\u003e9.2 Fuzzy Integrals 188\u003c\/p\u003e \u003cp\u003e9.3 Training The Fuzzy Integrals 191\u003c\/p\u003e \u003cp\u003e9.4 Summary and Final Thoughts 203\u003c\/p\u003e \u003cp\u003eExercises 203\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III EVOLUTIONARY COMPUTATION 207\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Evolutionary Computation 209\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Basic Ideas and Fundamentals 209\u003c\/p\u003e \u003cp\u003e10.2 Evolutionary Algorithms: Generate and Test 216\u003c\/p\u003e \u003cp\u003e10.3 Representation, Search, and Selection Operators 221\u003c\/p\u003e \u003cp\u003e10.4 Major Research and Application Areas 223\u003c\/p\u003e \u003cp\u003e10.5 Summary 225\u003c\/p\u003e \u003cp\u003eExercises 225\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Evolutionary Optimization 227\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Global Numerical Optimization 229\u003c\/p\u003e \u003cp\u003e11.2 Combinatorial Optimization 233\u003c\/p\u003e \u003cp\u003e11.3 Some Mathematical Considerations 238\u003c\/p\u003e \u003cp\u003e11.4 Constraint Handling 255\u003c\/p\u003e \u003cp\u003e11.5 Self-Adaptation 258\u003c\/p\u003e \u003cp\u003e11.6 Summary 264\u003c\/p\u003e \u003cp\u003eExercises 265\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. Evolutionary Learning and Problem Solving 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Evolving Parameters of A Regression Equation 270\u003c\/p\u003e \u003cp\u003e12.2 Evolving The Structure and Parameters of Input–Output Systems 274\u003c\/p\u003e \u003cp\u003e12.3 Evolving Clusters 292\u003c\/p\u003e \u003cp\u003e12.4 Evolutionary Classification Models 298\u003c\/p\u003e \u003cp\u003e12.5 Evolutionary Control Systems 307\u003c\/p\u003e \u003cp\u003e12.6 Evolutionary Games 314\u003c\/p\u003e \u003cp\u003e12.7 Summary 320\u003c\/p\u003e \u003cp\u003eExercises 321\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13. Collective Intelligence and Other Extensions of Evolutionary Computation 323\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Particle Swarm Optimization 323\u003c\/p\u003e \u003cp\u003e13.2 Differential Evolution 326\u003c\/p\u003e \u003cp\u003e13.3 Ant Colony Optimization 329\u003c\/p\u003e \u003cp\u003e13.4 Evolvable Hardware 331\u003c\/p\u003e \u003cp\u003e13.5 Interactive Evolutionary Computation 333\u003c\/p\u003e \u003cp\u003e13.6 Multicriteria Evolutionary Optimization 335\u003c\/p\u003e \u003cp\u003e13.7 Summary 340\u003c\/p\u003e \u003cp\u003eExercises 340\u003c\/p\u003e \u003cp\u003eReferences 343\u003c\/p\u003e \u003cp\u003eIndex 361\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407008997719,"sku":"9781119214342","price":89.1,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119214342.jpg?v=1730497870","url":"https:\/\/bookcurl.com\/products\/fundamentals-of-computational-intelligence-9781119214342","provider":"Book Curl","version":"1.0","type":"link"}