带混合学习算法的多阶段神经模糊系统模型

Abstract

Abstract: A multistage Neural Fuzzy System (NFS) model based on syllogistic fuzzy reasoning is proposed in this paper. From the stipulated inputoutput data pairs, an appropriate syllogistic fuzzy rule set can be generated via structure learning (using Genetic Algorithm) and parameter learning (using Backpropagation Neural Network) proceduresproposed in this paper. In addition, by means of solving Benchmark problem and unmanned vehicl control problem, we discussed and analyzed the performance of the proposed model in terms of effectiveness and robustness as compared with singlestage NFS models.

Key words: hybrid learning algorithm, multistage neural fuzzy system, syllogistic fuzzy reasoning

CLC Number:

TP183

YIN Shuyou, HUANG Lan. Model of Multistage Neural Fuzzy System withHybrid Learning Algorithm[J].J4, 2008, 46(01): 89-95.

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Model of Multistage Neural Fuzzy System withHybrid Learning Algorithm

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