EVALUATING WEAPONS SYSTEM USING FUZZY APPROXIMATE REASONING | ||||
| The International Conference on Mathematics and Engineering Physics | ||||
| Article 6, Volume 5, International Conference on Mathematics and Engineering Physics (ICMEP-5), May 2010, Page 1-11 PDF (239.18 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/icmep.2010.29774 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Mahmod Othman; Ku Ruhana Ku-Mahamud; Mohamad Fadhili Yahaya | ||||
| Abstract | ||||
| Abstract: This paper proposed the application of the fuzzy evaluation model using fuzzy sets and approximate reasoning. The objective of the study is to evaluate the weapon system in a subjective environment. The proposed method 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 reasoning 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 decisionmaking 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 option and less dependency on the domain of experts. Finally, we constructed a practical example for evaluating attack helicopters to demonstrate the proposed method. From these results, the proposed method shows outstanding performance in comparing with Cheng et al.’s method with 100% accuracy in ranking three attack helicopter alternatives, S1 (MI-28), S2 (AH-64, and S3 (AH-1w). Again the subjective evaluation method showed the advantages of simpler rules properties in NR , Max_L and Min_L. This research work has achieved its objective and produced good evaluation results. This portrays its major advantages in making decisions in new cases, where there is limited or an absence of specific knowledge. | ||||
| Keywords | ||||
| Fuzzy sets; Multi-criteria decision making; approximate reasoning | ||||
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