Generation of Interpretable Fuzzy System Based on Evolution Strategy

YAN Ling; ZHENG Hong-tao; JIANG Jing-ping

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Generation of Interpretable Fuzzy System Based on Evolution Strategy

更新时间：2025-07-16

- Generation of Interpretable Fuzzy System Based on Evolution Strategy
- Acta Electronica Sinica Vol. 33, Issue 1, Pages: 70-73(2005)
- 作者机构：
  
  浙江大学电气工程学院,浙江,杭州,310027
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP273TP30
- Published：2005
- 稿件说明：
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YAN Ling, ZHENG Hong-tao, JIANG Jing-ping. Generation of Interpretable Fuzzy System Based on Evolution Strategy[J]. Acta Electronica Sinica, 2005, 33(1): 70-73.
DOI：

YAN Ling, ZHENG Hong-tao, JIANG Jing-ping. Generation of Interpretable Fuzzy System Based on Evolution Strategy[J]. Acta Electronica Sinica, 2005, 33(1): 70-73. DOI：

摘要

模糊系统的可解释性明显优于其他人工智能方法

却长期没有引起人们足够的注意.本文对模糊系统的可解释性作了深入的分析

定义了最简约模糊划分、模糊划分的完备-清晰性、模糊规则的完备性、紧凑性和一致性

并将其加入到进化策略的适值函数中

用于优化模糊系统.仿真试验表明

即使在先验知识较少的情况下

该方法依然可以设计出具有较好系统响应性能和较高可解释性的模糊系统.

Abstract

The minimal fuzzy partition

completeness and distinguishability of fuzzy partition

and consistency of rule are defined

with further analysis on Interpretability.In an attempt to develop interpretable fuzzy systems

a systematic design paradigm is proposed using evolution strategy for mixed parameter optimization.The proposed approach is applied to the design of fuzzy controller for a nonlinear plant.It is verified that the interpretable fuzzy system works very well

especially when the priori Knowledge are insufficient.

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