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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...
Recently, cost-sensitive data mining has been an area of extensive research interests. Intelligent ant colony classification algorithm is introduced in cost-sensitive data mining method in order to obtain satisfied classification results by interaction of ant individuals. The convergence rate of classification is increased by using of metacost's meta-learning theory. Moreover, Boosting theory is investigated...
Introducing the rank-weight method into the basic ant colony optimization (ACO), we use the modified ACO to optimize the weights and thresholds value of neural networks (NN). And when the BPNN is being trained, this method can solve the disadvantages of running into the minimum easily, and enhance the convergence speed. So we get a heuristic method, which is good at time efficiency and derivation...
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