An argument-dependent approach to determining OWA operator weights based on the rule of maximum entropy: Research Articles

Authors:
Jian Wu;Chang-Yong Liang;Yong-Qing Huang
Affiliations:
Department of Management, HeFei University of Technology, HeFei230009, People's Republic of China;Department of Management, HeFei University of Technology, HeFei230009, People's Republic of China;Department of Management, HeFei University of Technology, HeFei230009, PRC and Institute of Information Engineering, Xuzhou Normal University,Xuzhou221011, PRC
Venue:
International Journal of Intelligent Systems
Year:
2007

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Abstract

The methods for determining OWA operator weights have aroused wide attention. We first review the main existing methods for determining OWA operator weights. We next introduce the principle of maximum entropy for setting up probability distributions on the basis of partial knowledge and prove that Xu's normal distribution-based method obeys the principle of maximum entropy. Finally, we propose an argument-dependent approach based on normal distribution, which assigns very low weights to these “false” or “biased” opinions and can relieve the influence of the unfair arguments. A numerical example is provided to illustrate the application of the proposed approach. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 209–221, 2007.