Application of neural networks with linear and nonlinear weights in occupational disease incidence forecast

This paper proposes the application of Artificial Neural Networks (ANN) in forecasting miners´ occupational disease incidence, examines the effect of BP network topology and parameters on training time, describes a neural network that uses Legendre polynomials as nonlinear weights and tries to find the most suitable network model to solve the problem via analyzing the forecast result. Through computer simulation, it clarifies that this model could forecast miners´ pneumoconiosis incidence commendably