Integration of Unascertained Method and Neural Networks in Financial Early Warning

Unascertained system that imitates the human brain´s thinking logical is a kind of mathematical tools used to deal with imprecise and uncertain knowledge. Artificial neural network that imitates the function of human neurons may function as a general estimator, mapping the relationship between input and output. Combination of these two methods were made attemption in financial early warning in this paper. Application case shows that combines unascertained systems with feedforward artificial neural networks can obtain more reasonable and more advantage of nonlinear mapping that can handle more complete type of data.