基于特征点的模糊推理系统

Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI:10.1109/AFSS.1996.583691

T. Yin, C.S.G. Lee

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引用次数: 5

摘要

提出了一种基于特征点的模糊推理系统(CPFIS)，用于对复杂系统的输入输出关系进行建模。结果表明，人工智能系统的推理操作是基于模糊规则之间的插值，模拟了人类的总结能力。提出的CPFIS提供了一种系统的方法，通过与人类推理的插值特性相关的最大和最小模糊规则以及它们对插值特性的应用，来构建具有插值特性的模糊规则库，从而使高维系统的模糊规则库较小。

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A characteristic-point-based fuzzy inference system

A fuzzy inference system (FIS), called characteristic point based fuzzy inference system (CPFIS), is proposed to model the input output relationship of a complex system. It is observed that the inference operations of FISs are based on the interpolations among the fuzzy rules which emulate the summarizing ability of human beings. The proposed CPFIS provides a systematic method to constructing FISs via the interpolation property with two distinct features: maximum and minimum fuzzy rules which are related to the interpolation property of human reasoning, and their employment for the interpolation property, resulting in a small sized fuzzy rule base for high dimensional systems.

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Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium

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