水资源与水工程学报2012，Vol.23Issue(6)：6-9,4.
基于主成分分析的BP神经网络对南京市水资源需求量预测
Forecast of water demand by using BP neutral network based on principle component analysis in Nanjing
摘要
Abstract
Taking the water demand data from 1999 to 2010 of Nanjing for example, this paper analyzes the main factors that influence the water resource quantity based on the principle component analysis method. According to these main factors, the input samples of BP neutral network are determined. Thereby, the BP neutral networks can be trained to predict. The results show that population, GDP, wa-ter consumption of ten thousand yuan GDP, water resources per capita and volume of sewage discharge per year are the primary indexes that affect water resource demand. The corresponding prediction model-ing outcome shows that the simulated experiment is quite fit for the practical situation and the average er-ror of prediction is less than 0. 2 × 108 m3 .关键词
需水预测/主成分分析法/BP神经网络Key words
water demand prediction/ principle component analysis/ BP neutral networks分类
建筑与水利引用本文复制引用
王春娟,冯利华,罗伟..基于主成分分析的BP神经网络对南京市水资源需求量预测[J].水资源与水工程学报,2012,23(6):6-9,4.基金项目
国家自然科学基金项目(41171430、40771044) （41171430、40771044）
