A LEARNING METHOD OF FUZZY REASONING BY GENETIC ALGORITHMS

A LEARNING METHOD OF FUZZY REASONING BY GENETIC ALGORITHMS
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一种基于遗传算法的模糊推理学习方法

DOI：
10.1103/physreve.71.036116
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发表时间：
1993
期刊：
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
影响因子：
--
通讯作者：
F. Herrera
F. Herrera
中科院分区：
--
文献类型：
--
作者：
J. Castro;M. Delgado;F. Herrera

文献摘要

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模糊规则库系统（FRBS）已被证明是一个重要的工具，在问题，由于复杂性或不精确，经典的工具是不成功的。在[3,14]中已经证明了快速射电暴是普遍逼近器，这意味着对于任何连续系统都可以找到一组能够以任意精度逼近它的模糊规则。现在的问题是：我们如何找到这一套规则？
Fuzzy Rule Base Systems (FRBS) has been shown to be an important tool for problems where, due to the complexity or the imprecision, classical tools are unsuccessful. In [3,14] it has been proved that FRBS are universal approximators in the sense that for any continuous system it is possible to find a set of fuzzy rules able of approximating it with arbitrary accuracy. Now, the question is: How can we find this set of rules?.