| 三种城市日用水量预测模型对比研究 |
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| 引用本文： | 杨东豫,吕谋,谭周吉.三种城市日用水量预测模型对比研究[J].青岛建筑工程学院学报,2011(2):74-79. |
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| 作者姓名： | 杨东豫 吕谋 谭周吉 |
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| 作者单位： | [1]青岛理工大学环境与市政工程学院,青岛266033 [2]青岛三龙城建综合开发有限公司,平度266700 |
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| 基金项目： | 国家自然科学基金资助项目（50878108） |
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| 摘 要： | 为实现科学、安全供水,建立精度高、可靠性强的城市日用水量预测模型,分别运用单指数平滑法、灰色预测方法、BP神经网络三种方法,对A市进行城市日用水量预测,并具体分析了各种方法的优缺点及适用范围.通过优化对比分析,当基础数据较完善时,BP神经网络预测模型精度较高,能较好地满足预测要求.
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| 关 键 词： | 城市日用水量 短期预测 单指数平滑法 灰色预测模型 BP神经网络 |
Contrastive Research on Three Forecasting Models of Daily Urban Water Consumption |
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| YANG Dong-yu,L Mou,TAN Zhou-ji.Contrastive Research on Three Forecasting Models of Daily Urban Water Consumption[J].Journal of Qingdao Institute of Architecture and Engineering,2011(2):74-79. |
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| Authors: | YANG Dong-yu L Mou TAN Zhou-ji |
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| Affiliation: | 1.School of Environmental and Municipal Engineering,Qingdao Technological University,Qingdao 266033,China;2.Qingdao Three Dragon Urban Construction Integrated Development Co.,Ltd.,Pingdu 266700,China) |
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| Abstract: | In order to realize a scientific and safe water supply and achieve the accuracy and reliability of the forecasting model of daily urban water consumption,the daily urban water consumption of A city is predicted by using the single exponential smoothing,gray prediction method and BP neural network.The advantages and disadvantages and ranges of application of each method are analyzed in detail.Through comparative analysis by optimizing,when the basic datum is perfect,the BP neural network model has a higher precision and it can preferably meet the forecast requirements. |
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| Keywords: | daily urban water consumption short-term prediction single exponential smoo-thing gray prediction model BP neural network |
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