基于模糊集和粗糙集的鲁棒函数逼近

Chih-Ching Hsiao
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引用次数: 0

摘要

粗糙集理论是处理不精确、不完整或不确定信息系统的成功方法。模糊集和粗糙集理论被证明特别适合分析各种类型的数据,特别是当处理不精确、不确定或模糊的知识时。在本文中,我们提出了一种新的算法,称为粗糙-模糊c -回归模型(RFCRM),它以模糊回归的方式定义模糊子空间,并将粗糙集理论用于TSK建模,具有对异常值的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust function approximation based on fuzzy sets and rough sets
The rough set theory is successes to deal with imprecise, incomplete or uncertain for information system. Fuzzy set and the rough set theories turned out to be particularly adequate for the analysis of various types of data, especially, when dealing with inexact, uncertain or vague knowledge. In this paper, we propose an novel algorithm, which termed as Rough-Fuzzy C-regression model (RFCRM), that define fuzzy subspaces in a fuzzy regression manner and also include Rough-set theory for TSK modeling with robust capability against outliers.
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