Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications / Edition 1by Okyay Kaynak
Pub. Date: 10/01/1998
Publisher: Springer Berlin Heidelberg
Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision. This book is based on a NATO Advanced Study Institute held in 1996 on soft computing and its
Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision. This book is based on a NATO Advanced Study Institute held in 1996 on soft computing and its applications. The distinguished contributors consider the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications. Two areas emphasized in the book are how to achieve a synergistic combination of the main constituents of soft computing and how the combination can be used to achieve a high Machine Intelligence Quotient.
Table of Contents
1 Computational Intelligence.- Roles of Soft Computing and Fuzzy Logic in the Conception, Design and Deployment of Information/Intelligent Systems.- Computational Intelligence Defined — By Everyone!.- Computational Intelligence: Extended Truth Tables and Fuzzy Normal Forms.- Uncertainty Theories by Modal Logic.- 2 Foundations of Fuzzy Theory.- Sup-T Equations: State of the Art.- Measures of Specificity.- What’s in a Fuzzy Membership Value?.- New Types of Generalized Operations.- 3 Fuzzy Systems.- Intelligent Fuzzy System Modeling.- Fuzzy Inference Systems: A Critical Review.- Fuzzy Decision Support Systems.- Neuro-Fuzzy Systems.- Fuzzified Petri-Nets and Their Application to Organising Supervisory Controller.- 4 Neural Networks.- A Review of Neural Networks with Direct Learning Based on Linear or Non—linear Threshold Logics.- The Morphogenetic Neuron.- Boolean Soft Computing by Non—linear Neural Networks with Hyperincursive Stack Memory.- 5 Data Analysis.- Using Competitive Learning Models for Multiple Prototype Classifier Design.- Fuzzy Data Analysis.- Probabilistic and Possibilistic Networks and How To Learn Them from Data.- 6 Applications.- Image Pattern Recognition Based on Fuzzy Technology.- Fuzzy Sets and the Management of Uncertainty in Computer Vision.- Intelligent Robotic Systems Based on Soft Computing—Adaptation, Learning and Evolution.- Hardware and Software Architectures for Soft Computing.- Fuzzy Logic Control for Design and Control of Manufacturing Systems.- Applications of Intelligent Multiobjective Fuzzy Decision Making.- A Product Life Cycle Information Management System Infrastructure with CAD/CAE/CAM, Task Automation, and Intelligent Support Capabilities.
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