文章摘要
赵 强, 徐征和, 苏万敏.基于RBF神经网络的城市需水量预测——以济南市为例Journal of Water Resources and Water Engineering[J].,2013,24(6):124-127
基于RBF神经网络的城市需水量预测——以济南市为例
Urban water demand forecast based on RBF neural network:a case study of Jinan
  
DOI:10.11705/j.issn.1672-643X.2013.06.029
中文关键词: 需水量预测  RBF神经网络  济南市
英文关键词: urban water demand forecast  RBF neural network  Jinan city
基金项目:山东省科技发展计划项目(2010GSF10630); 济南市科学技术发展计划项目(201101089)
Author NameAffiliation
ZHAO Qiang1,2, XU Zhenghe1,2, SU Wanmin1 (1.济南大学 资源与环境学院 山东 济南 2500222.山东省地下水数值模拟与污染控制工程技术研究中心 山东 济南 250022) 
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中文摘要:
      以济南市需水量为研究对象,运用径向基函数(RBF)神经网络建立预测模型,用1996-2008年13年济南市需水量数据,分析影响需水量的因素,确定多个关键因子,以Matlab为平台实现网络的训练,然后对2009年-2011年3年需水量进行预测检验。结果表明:预测相对误差较小,预测结果和实际情况吻合较好,可以对济南市未来规划年的需水量进行预测。在研究结果基础上,结合本文成果与出现的问题,对需水量预测方法等方面进行了探讨与展望,为以后需水预测研究提供一定的参考依据。
英文摘要:
      Taking the water demand of Jinan as a study object, combining with the historical water demand data in thirteen years, the paper analyzed the factors that affect water demand and determine a number of key factors and then used Matlab platform to realize network training, and predicted the water demand of three years from 2009 to 2011. The results show that the relative forecast error is small, and the predicted results agree well with the actual situation, so the method can be used to forecast the water demand of Jinan city in future planning years. On the basis of research result, it discussed and prospected the method of water demand prediction by combining with the paper achievement and problems, witch can provide references for the future research of water demand forecast.
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