Excluded-Mean-Variance Neural Decision Analyzer for Qualitative Group Decision Making

  • Song K
  • Kozinski J
  • Seniuk G
  • et al.
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper we introduce an innovative approach to group decision making in uncertain situations by using a mean-variance neural approach. The key idea of this proposed approach is to compute the excluded mean of individual evaluations and weight it by applying a variance influence function (VIF); this process of weighting the excluded mean by VIF provides an improved result in the group decision making. In this paper, a case study with the proposed excluded-mean-variance approach is also presented. The results of this case study indicate that this proposed approach can improve the effectiveness of qualitative decision making by providing the decision maker with a new cognitive tool to assist in the reasoning process.

Cite

CITATION STYLE

APA

Song, K.-Y., Kozinski, J., Seniuk, G. T. G., & Gupta, M. M. (2012). Excluded-Mean-Variance Neural Decision Analyzer for Qualitative Group Decision Making. Advances in Fuzzy Systems, 2012, 1–10. https://doi.org/10.1155/2012/204864

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free