Research on BP Neural Network Model for Water Demand Forecasting and Its Application

被引：2
|
作者：
Sun Yuefeng [1 ]
Chang Haotian [2 ]
Mia Zhengjian [2 ]
机构：
[1] Tianjin Polytech Univ, Sch Management, Tianjin 300387, Peoples R China
[2] Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China
来源：
PROGRESS IN CIVIL ENGINEERING, PTS 1-4 | 2012年 / 170-173卷
基金：
中国国家自然科学基金;
关键词：
BP neural network; water demand forecasting; basin; water resource management;
D O I：
10.4028/www.scientific.net/AMM.170-173.2352
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
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 m(3) in 2015 and 43.6 billion m(3) in 2030 in the study area. The results are useful for water resources planning and management.
引用
收藏
页码：2352 / +
页数：2
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