模式识别与人工智能
Tuesday, Apr. 22, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2007, Vol. 20 Issue (3): 343-348    DOI:
Papers and Reports Current Issue| Next Issue| Archive| Adv Search |
Fuzzy MultiAttribute Group Decision Making Methods Based on Structured Element
LIU HaiTao, GUO SiZong
College of Science, Liaoning Technical University, Fuxin 123000

Download: PDF (336 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  The purpose of this paper is to introduce the structured element theory into fuzzy multiattribute decision making, and to simplify the complex operations of traditional fuzzy decision making. The compromised group decision making method is one of the most commonly methods in classical multiattribute group decision making. According to the principle of this method , two kinds of fuzzy compromised group decision making methods based on the structured element theory are put forward. The decision making is carried out by using the example from Transformation Group of Monotone Functions with Same Monotonic Formal on [-1,1] and Operations of Fuzzy Numbers by Sizong Guo. Finally, the proposed methods are compared with the traditional decision making methods. The proposed methods have a reference value to the fuzzy multiattribute group decision making problems.
Key wordsFuzzy MultiAttribute Group Decision Making      Fuzzy Structured Element      Maximum Function      Minimum Function      Hamming Distance     
Received: 04 July 2006     
ZTFLH: O159  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
LIU HaiTao
GUO SiZong
Cite this article:   
LIU HaiTao,GUO SiZong. Fuzzy MultiAttribute Group Decision Making Methods Based on Structured Element[J]. , 2007, 20(3): 343-348.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I3/343
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn