一种基于模糊加权推理的模糊神经网络方法

Proceedings 2000 International Workshop on Autonomous Decentralized System (Cat. No.00EX449) Pub Date : 2000-09-21 DOI:10.1109/IWADS.2000.880906

Zhou Chunguang, Liang Yanchun, Yang Zhimin

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引用次数: 2

摘要

在Mamdani推理方法的基础上，提出了一种改进的模糊加权推理方法。在改进模糊加权推理方法的基础上，提出了一种模糊神经网络。利用遗传算法进行网络权值的训练和隶属函数的优化。模糊规则可以根据网络的权重得到。仿真实验验证了网络模型和算法的有效性。

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A fuzzy neural network based on fuzzy weighted reasoning method

An improved fuzzy weighted reasoning method is presented on the basis of the 'Mamdani' reasoning method. A fuzzy neural network is developed based on the improved fuzzy weighted reasoning method. The training of network weights and optimization of membership functions are conducted using genetic algorithms. Fuzzy rules can be obtained according to the weights of the network. The effectiveness of the network model and the algorithm is examined by simulated experiments.

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Proceedings 2000 International Workshop on Autonomous Decentralized System (Cat. No.00EX449)

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