Wavelet Neural Network Model Application on the Case Selection of Tax Check in Real Estate Industry

The case selecting of tax check in real estate industry has been the subject of considerable research effort in recent years. In this paper, we propose Wavelet neural networks (WNN) for it, which used in many fields because of their advantages over neural network and wavelet analysis as they achieve faster convergence and discriminance more precise. A suit of evaluation indices are constructed as well as the WNN's applying model. Finally, simulation tests are developed on it. Experimental results verify that its convergent velocity and discriminant precision are quickly and steadily achieved, and shows its better performance than Back-Propagation neural network (BPNN) and multiple linear discriminance analysis (MLDA).