Research on BP Neural Network Model for Water Demand Forecasting and its Application
It is difficult to determine a proper neurons number of the mid-layer when using the BP neural network for water demand forecasting. Aiming at the problem, the BP neural network is presented in this paper for water demand forecasting. A suitable neurons number in the mid-layer is calculated based on the empirical formula method and trial and error method. A certain basin in China is taken as a case study. The results indicate that the mean relative error is 2.42%. The water consumption is 42.8 billion m3 in 2015 and 43.6 billion m3 in 2030 in the study area. The results are useful for water resources planning and management.
Mingjin Chu, Xiangran Li, Jingzhou Lu, Xingmin Hou and Xiaogang Wang
Y. F. Sun et al., "Research on BP Neural Network Model for Water Demand Forecasting and its Application", Applied Mechanics and Materials, Vols. 170-173, pp. 2352-2355, 2012