Statistical-Fuzzy Approach to Quantify Cumulative Impact of Change Orders

This paper presents a hybrid approach to quantify the impact of change orders on construction projects using statistical regression and fuzzy logic. There are many qualitative variables affecting the impact of change orders on labor productivity; statistical analysis falls short of addressing the fuzziness of those variables. Because of their complementary nature, fuzzy logic and regression analysis can be integrated; regression analysis is used to determine the membership functions of the input linguistic values. In this paper, each input variable is statistically treated before entering a general rule relating its space to the space of loss in labor productivity. The relative weight of each input variable is determined by its coefficient of determination (R2) value. The expected loss of labor productivity and its standard deviation are then determined from the output fuzzy membership function. The proposed methodology is general and can be applied in areas of system analysis and decision making when a complex input-output function is to be predicted in the presence of some fuzzy knowledge and a large number of real input-output data.