En savoir plus
Informationen zum Autor LEFTERI H. TSOUKALAS, PhD, is on the faculty of the School of Nuclear Engineering at Purdue University and is an active industrial consultant and speaker. ROBERT E. UHRIG, PhD, holds a joint appointment as Distinguished Professor in the Nuclear Engineering Department at the University of Tennessee and Distinguished Scientist in the Instrumentation and Control Division at the Oak Ridge National Laboratory. He is the author of Random Noise Techniques in Nuclear Reactor Systems. Klappentext Provides a truly accessible introduction and a fully integrated approach to fuzzy systems and neural networks-the definitive text for students and practicing engineers Researchers are already applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. But the integration of these two fields into a "neurofuzzy" technology holds even greater potential benefits in reducing computing time and optimizing results. Fuzzy and Neural Approaches in Engineering presents a detailed examination of the fundamentals of fuzzy systems and neural networks and then joins them synergistically-combining the feature extraction and modeling capabilities of the neural network with the representation capabilities of fuzzy systems. Exploring the value of relating genetic algorithms and expert systems to fuzzy and neural technologies, this forward-thinking text highlights an entire range of dynamic possibilities within soft computing. With examples specifically designed to illuminate key concepts and overcome the obstacles of notation and overly mathematical presentations often encountered in other sources, plus tables, figures, and an up-to-date bibliography, this unique work is both an important reference and a practical guide to neural networks and fuzzy systems. Zusammenfassung Fuzzy Logic und neuronale Netze, bisher zwei relativ unabhängige Technologien mit überragendem Erfolg, werden in diesem Werk verknüpft. Anhand detaillierter Beispiele werden dem Elektronikingenieur oder Softwaredesigner die erstaunlichen Synergieeffekte nahegebracht, die die kombinierte Anwendung beider Techniken ermöglicht. Inhaltsverzeichnis Aus dem Inhalt: Introduction to Hybrid AI Systems; Foundations of Fuzzy Approaches; Fuzzy Relations; Fuzzy Numbers; Linguistic Descriptions and Their Analytical Forms; Fuzzy Control; Fundamentals of Neural Networks; Backpropagation and Related Training Algorithms; Competitive, Associative and Other Special Neural Networks; Dynamic Systems and Neural Control; Practical Aspects of Using Neural Networks; Neural Networks in Fuzzy Systems; Fuzzy Methods in Neural Networks; General Hybrid Neurofuzzy Applications; Dynamic Hybrid Neurofuzzy Applications; Role of Expert Systems in Fuzzy Neural Systems; Genetic Algorithms; Future Trends in Soft Computing...
