9780471160038: Fuzzy and Neural Approaches in Engineering

Sinossi

Die ingenieurtechnische Anwendung von Fuzzy Logic und neuronalen Netzen hat in letzter Zeit immer mehr an Bedeutung gewonnen. Dieses Handbuch enthält auf MATLAB basierende ergänzende Programme zu diesen Themen. Die beiliegende Diskette mit zugehörigen Programmtexten rundet das Werk ab.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.