DPSIR-BP Neural Network Based Section Multi-stage Optimal Configuration Model of Water Resources in Middle and Small Rivers
In order to rationally allocate water resources and improve the utilization rate of water resources and the shortage of water resources,a multi-stage optimal configuration model of water resources section of medium and small rivers based on DP-SIR-BP neural network is studied.An evaluation index system is established through the DPSIR model to calculate the water resources carrying capacity of the region,and the water resources supply range is divided by referring to the grade division ta-ble.The maximum comprehensive benefit of water use is taken as the objective function in the wet season,and the minimum difference between supply and demand of water resources is taken as the objective function in the dry season.Under the three constraints of water supply capacity,water demand change and non-negative value of variables,the optimal solution of the model is obtained through BP neural network,and the multi-stage optimal allocation scheme of water resources section in medi-um and small rivers is obtained.The results show that,the multi-stage optimal allocation scheme designed by the studied model has the largest comprehensive benefit of water use and the smallest difference between supply and demand of water resources,thus completing the multi-stage optimal allocation.
DPSIRBP neural networkmedium and small riverwater resources sectionmulti-stage optimal configuration
万方数据
维普
