傳統迴歸分析只適用於處理調查資料或變數為明確的數值，模糊迴歸分析則可處理主觀與非明確的資料。現存可處理因變數為梯形模糊數的模糊迴歸模式甚少，且存在計算困難之問題，以及尚無可衡量模式配適度方法。因此，本研究提出一可處理非對稱梯形模糊輸出資料的迴歸分析法，迴歸式的建立係以線性規劃法求解模糊度最小而得。此外，本研究亦提出一分析方法來衡量其模式配適的品質。最後，本研究以橋樑伸縮縫狀況為案例，來探討模式的實用性與預測伸縮縫狀況。

Ordinary regression techniques only suit to deal with crisp inspected data. Fuzzy regression model can solve subjective and non-crisp data. There are fewer linear regression model talking about trapezoidal fuzzy data, and their shortage are hardly calculated. There does not exist a model to test goodness of fit of the result of regression model. Therefore, this study presents a model to solve asymmetry trapezoidal fuzzy output data with minimizing vagueness by linear- programming method. Besides , this study built up a method to test the goodness of fit of the result of estimation. At last, this study show an application of linear regression analysis with trapezoidal fuzzy data, called prediction of condition of bridge deck expansion joint.

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