An improved fuzzy synthetic evaluation using expanded optimization algorithm for combining index weights

doi:10.1109/CCDC.2008.4597733

	An improved fuzzy synthetic evaluation using expanded optimization algorithm for combining index weights
	Chen, Wei; Hao, Xiaohong; Lin, Jie
	2008
会议日期	July 2, 2008 - July 4, 2008
会议地点	Yantai, Shandong, China
关键词	Maximum principle Optimization Degree of membership Fuzzy synthetic evaluation Index weight Matrix of fuzzy relations Maximum degree Optimization algorithms Optimization method Sequential segmentation
DOI	10.1109/CCDC.2008.4597733
页码	2296-2299
英文摘要	Fuzzy synthetic evaluation is usually be influenced significantly by the matrix of fuzzy relation and index vector. For a sequential segmentation category, the principle of the lowest cost, the principle of maximum degree of measure and the principle of maximum degree of membership sometimes can get unreasonable conclusion, even sometimes can get error conclusion, because they conceal the difference of two degree of membership. First of all, a new expanded optimization algorithm is presented for combining index weights, then bring out a improved fuzzy synthetic evaluation method based on reliability code. The proposed method can overcome the shortages of the traditional fuzzy synthetic evaluation. Case results clearly show that the proposed method is attractive and effective. © 2008 IEEE.
会议录	Chinese Control and Decision Conference, 2008, CCDC 2008
会议录出版者	IEEE Computer Society
语种	中文
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116875]
专题	电气工程与信息工程学院
作者单位	College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
推荐引用方式 GB/T 7714	Chen, Wei,Hao, Xiaohong,Lin, Jie. An improved fuzzy synthetic evaluation using expanded optimization algorithm for combining index weights[C]. 见:. Yantai, Shandong, China. July 2, 2008 - July 4, 2008.