A Grey Machine Learning Model with application to time series

the Grey Machine Learning Model based Variable Separable (VSGML) is presented in this paper. The VSGML´s function set is composed of the variable separable function. The Divide-and-Conquer architecture based Radial Basis Function (DCRBF) Network is constructed to implement VSGML. This DCRBF is composed of several sub-RBF networks which takes each sub-space as its input. The output of DCRBF is the sum of each sub-RBF networks´ output. The algorithm of DCRBF is given and its approximation ability also is discussed in this paper. The experimental results have shown that the DCRBF is outperforms the conventional RBF.