This paper, as traditional neural network suffers from the problems like the existence of many local minima and the choice of the number of hidden units, and over fiting ameliorate least squares support vector machine is proposed to predict the Hydropower Water volume. Case study shows that ameliorate least squares support vector machine based Hydropower Water volume forecast model has better generalization ability than BP neural network-based forecast model.
NETL
NSTL
万方数据
维普
