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基于最小二乘拟合的模糊隶属函数构建方法
引用本文:袁杰,史海波,刘昶. 基于最小二乘拟合的模糊隶属函数构建方法[J]. 控制与决策, 2008, 23(11): 1263-1266,1271
作者姓名:袁杰  史海波  刘昶
作者单位:中国科学院,沈阳自动化研究所,沈阳,110016;中国科学院,研究生院,北京,100049;中国科学院,沈阳自动化研究所,沈阳,110016
基金项目:国家自然科学基金项目,国家863计划项目
摘    要:针对当前模糊隶属函数构造方法中存在的问题,提出一种构造模糊隶属函数方法.采用最小二乘法拟合离散数据来获得隶属函数.为减小拟合误差,采用了3项措施以达到预期目标.所构建的隶属函数,对任意输入物理量可直接得到其对应模糊语言变量的隶属度,从而有效避免专家指定隶属度的主观臆断性及不一致性.该方法简单、求解精度高,具有广泛适用性和较强的应用价值.仿真结果证实了该方法的有效性.

关 键 词:隶属函数  最小二乘  拟合  隶属度  模糊

Construction of fuzzy membership functions based on least squares fitting
YUAN Jie,SHI Hai-bo,LIU Chang. Construction of fuzzy membership functions based on least squares fitting[J]. Control and Decision, 2008, 23(11): 1263-1266,1271
Authors:YUAN Jie  SHI Hai-bo  LIU Chang
Affiliation:YUAN Jie1,2,SHI Hai-bo1,LIU Chang1,2(1.Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China,2.Graduate School,Beijing 100049,China)
Abstract:This paper proposes a approach for constructing fuzzy membership functions considering some problems existing in some current methods.The approach employs least squares to fit discrete data,and their membership functions are obtained.To decrease fitting errors,three measures are adopted.For any input datum,its corresponding membership degree can be obtained directly by the constructed membership function.Subjectivity and unconsistency generated by experts can be avoided.This approach has simplicity,high acc...
Keywords:Membership function  Least square  Fitting  Membership degree  Fuzzy  
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