Computational intelligence concepts to implementations
Russ Eberhart and Yuhui Shi have succeeded in integrating various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook, including lots of practical examples. -Shun-ichi Amari, RIKEN Brain Science Institute, JapanThis book is an excelle...
| Autor principal: | |
|---|---|
| Otros Autores: | |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Elsevier/Morgan Kaufmann Publishers
c2007.
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627080606719 |
Tabla de Contenidos:
- Front Cover; Computational Intelligence; Copyright Page; Table of Contents; Preface; Chapter 1. Foundations; Definitions; Biological Basis for Neural Networks; Behavioral Motivations for Fuzzy Logic; Myths about Computational Intelligence; Computational Intelligence Application Areas; Summary; Exercises; Chapter 2. Computational Intelligence; Adaptation; Self-organization and Evolution; Historical Views of Computational Intelligence; Computational Intelligence as Adaptation and Self-organization; The Ability to Generalize
- Computational Intelligence and Soft Computing versus Artificial Intelligence and Hard ComputingSummary; Exercises; Chapter 3. Evolutionary Computation Concepts and Paradigms; History of Evolutionary Computation; Evolutionary Computation Overview; Genetic Algorithms; Evolutionary Programming; Evolution Strategies; Genetic Programming; Particle Swarm Optimization; Summary; Exercises; Chapter 4. Evolutionary Computation Implementations; Implementation Issues; Genetic Algorithm Implementation; Particle Swarm Optimization Implementation; Summary; Exercises
- Chapter 5. Neural Network Concepts and ParadigmsNeural Network History; What Neural Networks are and Why They are Useful; Neural Network Components and Terminology; Neural Network Topologies; Neural Network Adaptation; Comparing Neural Networks and Other Information Processing Methods; Preprocessing; Postprocessing; Summary; Exercises; Chapter 6. Neural Network Implementations; Implementation Issues; Back-propagation Implementation; The Kohonen Network Implementations; Evolutionary Back-propagation Network Implementation; Summary; Exercises; Chapter 7. Fuzzy Systems Conceptsand Paradigms
- HistoryFuzzy Sets and Fuzzy Logic; The Theory of Fuzzy Sets; Approximate Reasoning; Developing a Fuzzy Controller; Summary; Exercises; Chapter 8. Fuzzy Systems Implementations; Implementation Issues; Fuzzy Rule System Implementation; Evolving Fuzzy Rule Systems; Summary; Exercises; Chapter 9. Computational Intelligence Implementations; Implementation Issues; Fuzzy Evolutionary Fuzzy Rule System Implementation; Choosing the Best Tools; Applying Computational Intelligence to Data Mining; Summary; Exercises; Chapter 10. Performance Metrics; General Issues; Percent Correct
- Average Sum-squared ErrorAbsolute Error; Normalized Error; Evolutionary Algorithm Effectiveness Metrics; Mann-Whitney U Test; Receiver Operating Characteristic Curves; Recall and Precision; Other ROC-related Measures; Confusion Matrices; Chi-square Test; Summary; Exercises; Chapter 11. Analysis and Explanation; Sensitivity Analysis; Hinton Diagrams; Computational Intelligence Tools for Explanation Facilities; Summary; Exercises; Bibliography; Index; About the Authors; Chapter 12. Case Study Summaries; Case Study Preview; Case Study 1: Detection of Electroencephalogram Spikes
- Case Study 2: Determining Battery State of Charge
