| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 95 === In recent years, the task of measuring the degree of similarity between fuzzy numbers plays an important role in fuzzy decision making, information fusion and fuzzy risk analysis. In this thesis, we present two similarity measures for generalized fuzzy numbers and interval-valued fuzzy numbers. It combines the concepts of geometric distance, the perimeter, height and center of gravity point of generalized fuzzy numbers and interval-valued fuzzy number, respectively. Moreover, we also presented an interval-valued fuzzy number adjusting algorithm. Based on proposed similarity measures, we propose two new methods for handling fuzzy risk analysis problems. The proposed fuzzy risk analysis methods can overcome the drawback of existing methods. They can deal with fuzzy risk analysis in a more intelligent and flexible manner.
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