Fuzzy Evaluation of Weapons System

This paper proposed to apply fuzzy sets and approximate reasonings to evaluate the weapons system. The objective of the study is to determine the ranking of the weapons system in a subjective environment. The proposed model based on fuzzy sets has initiated the idea of membership set score value evaluation of each criterion alternative. This enables the inclusion of requirements which are incomplete and imprecise. The approximate reasonings of the method allows the decision maker to make the best choice in accordance to human thinking and reasoning processes. The proposed model is based on fuzzy multi-criteria decision-making that consists of fuzzy rules. The use of fuzzy rules, which are extracted directly from input data in making evaluation, contributes to a better decision in selecting the best choice and is less dependent on the domain of expert. The dataset from previous research was used to validate the fuzzy evaluation model. Results from numerical examples are comparable to other fuzzy evaluation approaches. Copyright a 2005

[1]  A. Bakar,et al.  Ranking the river basin planning alternatives using fuzzy approximate reasoning , 2004 .

[2]  Azuraliza Abu Bakar,et al.  Fuzzy similarity function for ranking river basin planning alternatives , 2004 .

[3]  I. B. Turksen,et al.  Fuzzy expert systems for IE/OR/MS , 1992 .

[4]  W. Pedrycz,et al.  A fuzzy extension of Saaty's priority theory , 1983 .

[5]  Chu Feng Fuzzy multicriteria decision-making in distribution of factories: an application of approximate reasoning , 1995 .

[6]  Toshiyuki Yamashita,et al.  On a support system for human decision making by the combination of fuzzy reasoning and fuzzy structural modeling , 1997, Fuzzy Sets Syst..

[7]  Mao-Jiun J. Wang,et al.  Personnel placement in a fuzzy environment , 1992, Comput. Oper. Res..

[8]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[9]  Hsi-cheng Li,et al.  Job search and employment , 1994 .

[10]  I. Burhan Turksen,et al.  A fuzzy set preference model for consumer choice , 1994 .

[11]  W. Pedrycz,et al.  An introduction to fuzzy sets : analysis and design , 1998 .

[12]  Tzung-Pei Hong,et al.  Induction of fuzzy rules and membership functions from training examples , 1996, Fuzzy Sets Syst..

[13]  G. Liang,et al.  Application of a fuzzy multi-criteria decision-making model for shipping company performance evaluation , 2001 .

[14]  H. Lee-Kwang,et al.  Ranking fuzzy values with satisfaction function , 1994 .

[15]  Sonja Yrjo Olavi Petrovic-Lazarevic,et al.  Personnel Selection Fuzzy Model , 2001 .

[16]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .