Method and Application of Debris Flow Hazard Assessment Based on SIGA-BP Neural Network
Houcheng Liu · Journal of Chongqing Jiaotong University · 2010
The risk degree of debris flow is determined by dangerous factors of the debris flow. The dangerous factors are divided into primary and secondary factors. It is difficult to choose the most dangerous factor. BP neural network is optimalized by self-adaptive immune genetic algorithm (SIGA),and seven dangerous factors of Yunnan province are obtained. SIGA-BP neural network is also established,which is applied to forecasting data of 10 groups’debris flow,and more accurate forecasting results are obtained.