Using a new type of nonlinear integral for multi-regression: an application of evolutionary algorithms in data mining

We develop a nonlinear multi-regression model based on the Wang integral to describe a multi-input single-output system. In this model, in general, set function μ is nonadditive. The nonadditivity of μ describes the inherent interaction among the input attributes x₁ , x₂, ..., x_n. When the proper input-output data are available, by using the adaptive genetic algorithm shown in this paper, rather precise estimated values of parameter c, q, w and μ of the regression model can be obtained. Thus, the multi-input single-output system can be used to make prediction. That is to say, when the values of input attributes x₁, X₂, ..., X _n, are known, we can predict the output Y by calculating the nonlinear multi-regression