Titlebook: Intelligent Hybrid Systems; Fuzzy Logic, Neural Da Ruan Book 1997 Springer Science+Business Media New York 1997 Chaos.algorithms.filtering

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书目名称Intelligent Hybrid Systems影响因子(影响力)




书目名称Intelligent Hybrid Systems影响因子(影响力)学科排名




书目名称Intelligent Hybrid Systems网络公开度




书目名称Intelligent Hybrid Systems网络公开度学科排名




书目名称Intelligent Hybrid Systems被引频次




书目名称Intelligent Hybrid Systems被引频次学科排名




书目名称Intelligent Hybrid Systems年度引用




书目名称Intelligent Hybrid Systems年度引用学科排名




书目名称Intelligent Hybrid Systems读者反馈




书目名称Intelligent Hybrid Systems读者反馈学科排名

troponins

CHURL

Compass

Eeg332

Introduction to Fuzzy Systems, Neural Networks, and Genetic Algorithms for the following chapters. Focus is placed on (1) the similarities between the three technologies through the common keyword of . and (2) how to use these technologies at a practical or programming level.

叙述

Nonlinear System Identification with Neurofuzzy Methods fuzzy models are given. Their properties, advantages, and drawbacks are illustrated. In a more specific part a new algorithm for the construction of Takagi-Sugeno fuzzy systems is presented in detail. It is successfully applied to the identification of two nonlinear dynamic real-world processes.

municipality

collateral

旁观者

A Fuzzy Neural Network for Approximate Fuzzy Reasoning are compared with traditional neural networks; other fuzzy neural networks and conventional fuzzy reasoning approaches. The work demonstrates the advantage of a neurofuzzy approach and highlights the advantages of this architecture for a hardware realization.

flaggy

A New Approach of Neurofuzzy Learning Algorithmuzzy rule table used in usual fuzzy applications, so that the case of weak-firing can be well avoided, which is different from the conventional neurofuzzy learning algorithms. Moreover, we show the efficiency of the developed method by identifying nonlinear functions.