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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書目名稱Intelligent Hybrid Systems影響因子(影響力)




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書目名稱Intelligent Hybrid Systems網(wǎng)絡(luò)公開度




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書目名稱Intelligent Hybrid Systems被引頻次




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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.

敘述

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

旁觀者

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.