The application of ant colony algorithm and artificial neural network in tax assessment
Shuiling Mao, Wanggen Wan, Rui Wang, Yue Gao · 2010
Tax assessment is an important and complex task in tax administration. A large number of data is involved in the process. Hence, a scientific model is in demanding. In this paper, we present a model which integrates the ant colony algorithm into artificial neural network to improve the performance of neural network in judgment of whether the taxpayer is credible. In details, we use ant colony algorithm to train the weights of artificial neural network, and this method could avoid some defects of artificial neural network. The simulation result validates the effectiveness of our method.