In this thesis, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. First, we present a method for ranking generalized fuzzy numbers with different left heights and right heights. The proposed method considers the areas of the positive side, the areas of the negative side and the centroid values of generalized fuzzy numbers as the factors for calculating the ranking scores of generalized fuzzy numbers with different left heights and right heights. It can overcome the drawbacks of the existing fuzzy ranking methods. Based on the proposed fuzzy ranking method of generalized fuzzy numbers with different left heights and right heights, we propose a new method for dealing with fuzzy risk analysis problems. The proposed fuzzy risk analysis method provides us with a useful way to deal with fuzzy risk analysis problems based on generalized fuzzy numbers with different left heights and right heights.

In this thesis, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. First, we present a method for ranking generalized fuzzy numbers with different left heights and right heights. The proposed method considers the areas of the positive side, the areas of the negative side and the centroid values of generalized fuzzy numbers as the factors for calculating the ranking scores of generalized fuzzy numbers with different left heights and right heights. It can overcome the drawbacks of the existing fuzzy ranking methods. Based on the proposed fuzzy ranking method of generalized fuzzy numbers with different left heights and right heights, we propose a new method for dealing with fuzzy risk analysis problems. The proposed fuzzy risk analysis method provides us with a useful way to deal with fuzzy risk analysis problems based on generalized fuzzy numbers with different left heights and right heights.

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