Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. This edited book comprises papers on diverse aspects of soft computing and hybrid intelligent systems. There are theoretical aspects as well as application papers. New methods and applications of hybrid intelligent systems using soft computing techniques are described. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of intelligent control, which are basically papers that use hybrid systems to solve particular problems of control. The second part contains papers with the main theme of pattern recognition, which are basically papers using soft computing techniques for achieving pattern recognition in different applications. The third part contains papers with the themes of intelligent agents and social systems, which are papers that apply the ideas of agents and social behavior to solve real-world problems. The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.
Author(s): Ricardo MartÃnez, Oscar Castillo, Luis T. Aguilar (auth.), Oscar Castillo, Patricia Melin, Janusz Kacprzyk, Witold Pedrycz (eds.)
Series: Studies in Computational Intelligence 154
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2008
Language: English
Pages: 448
Tags: Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)
Front Matter....Pages -
Front Matter....Pages 1-1
Optimization of Interval Type-2 Fuzzy Logic Controllers for a Perturbed Autonomous Wheeled Mobile Robot Using Genetic Algorithms....Pages 3-18
Fuzzy Control for Output Regulation of a Servomechanism with Backlash....Pages 19-28
Stability on Type-1 and Type-2 Fuzzy Logic Systems....Pages 29-51
Comparative Study of Type-1 and Type-2 Fuzzy Systems Optimized by Hierarchical Genetic Algorithms....Pages 53-70
Comparison between Ant Colony and Genetic Algorithms for Fuzzy System Optimization....Pages 71-86
Front Matter....Pages 87-87
Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and Its Optimization with Genetic Algorithms....Pages 89-114
Interval Type-2 Fuzzy Logic for Module Relevance Estimation in Sugeno Integration of Modular Neural Networks....Pages 115-127
Optimization of Response Integration with Fuzzy Logic in Ensemble Neural Networks Using Genetic Algorithms....Pages 129-150
Optimization of Modular Neural Network, Using Genetic Algorithms: The Case of Face and Voice Recognition....Pages 151-169
A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuzzy Logic....Pages 171-186
Front Matter....Pages 187-187
A Hybrid Model Based on a Cellular Automata and Fuzzy Logic to Simulate the Population Dynamics....Pages 189-203
Soft Margin Training for Associative Memories: Application to Fault Diagnosis in Fossil Electric Power Plants....Pages 205-230
Social Systems Simulation Person Modeling as Systemic Constructivist Approach....Pages 231-249
Modeling and Simulation by Petri Networks of a Fault Tolerant Agent Node....Pages 251-267
Fuzzy Agents....Pages 269-293
Front Matter....Pages 295-295
Design and Simulation of the Fuzzification Stage through the Xilinx System Generator....Pages 297-305
High Performance Parallel Programming of a GA Using Multi-core Technology....Pages 307-314
Scalability Potential of Multi-core Architecture in a Neuro-Fuzzy System....Pages 315-323
Methodology to Test and Validate a VHDL Inference Engine through the Xilinx System Generator....Pages 325-331
Modeling and Simulation of the Defuzzification Stage Using Xilinx System Generator and Simulink....Pages 333-343
Front Matter....Pages 345-345
A New Evolutionary Method Combining Particle Swarm Optimization and Genetic Algorithms Using Fuzzy Logic....Pages 347-361
A Hybrid Learning Algorithm for Interval Type-2 Fuzzy Neural Networks: The Case of Time Series Prediction....Pages 363-386
Optimization of Artificial Neural Network Architectures for Time Series Prediction Using Parallel Genetic Algorithms....Pages 387-399
Optimized Algorithm of Discovering Functional Dependencies with Degrees of Satisfaction Based on Attribute Pre-scanning Operation....Pages 401-415
A Fuzzy Symbolic Representation for Intelligent Reservoir Well Logs Interpretation....Pages 417-426
How to Solve a System of Linear Equations with Fuzzy Numbers....Pages 427-436
Design and Implementation of a Hybrid Fuzzy Controller Using VHDL....Pages 437-446
Back Matter....Pages -
