Multi-factor Estimation Model Based on Rough Set and BP Artificial Neural Network

【Abstract】In term of the important degree of input influence factor to output, rough set approach and the conception of information entropy are employed to reduce the parameters of the input parameter set with no changing classification quality of samples. Thus, the number of the input variables and neurons is gotten, and the multi-factor estimation model based on rough set and BP artificial network is set by learning from the typical samples. Its application to the cost estimation of missile system is given. It is shown that the approach can reduce the training time, improve the learning efficiency, enhance the predication accuracy, and be feasible and effective. 【Key words】Rough set; Neural network; Information entropy; Multi-factor estimation; Cost estimation