一种基于PSO和NHL算法的模糊认知图训练混合方法

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI:10.1109/IS.2008.4670458

M. N. Yazdi, C. Lucas

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引用次数: 0

摘要

本文提出了一种新的混合模糊认知图训练方法。fcm基于人类专家的知识，由于专家可能出现的错误，可能不够准确。因此，已经研究了一些学习方法来训练fcm，以便涵盖这些可能的错误。针对某化工控制问题，介绍了两种学习方法PSO和NHL及其新的混合学习方法，并对其进行了实现和测试。

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A hybrid method using PSO and NHL algorithms to train Fuzzy Cognitive Maps

In this paper a new hybrid method for training fuzzy cognitive maps is presented. FCMs are based on the knowledge of human experts and may not be accurate enough because of probable mistakes of experts. Thus, some learning methods have been investigated to train FCMs, so that these probable mistakes are covered. Two learning methods, PSO and NHL, and a new hybrid of them are introduced and implemented and tested for a chemical control problem.

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2008 4th International IEEE Conference Intelligent Systems

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