| Cite this article: | 杨存满,鞠佳伟,袁芳,等.基于BP神经网络的城市自来水厂供水量预测研究[J].灌溉排水学报,,():-. |
| Yang cunman,Ju jiawei,Yuan fang,et al.基于BP神经网络的城市自来水厂供水量预测研究[J].灌溉排水学报,,():-. |
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| DOI： |
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| Prediction model of water-supply of urban waterworks based on BP neural network |
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Yang cunman1, Ju jiawei1, Yuan fang2, Li xiaoshang3, Lan huachun1,4
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1.Research institute for environmental innovation(Suzhou), Tsinghua;2.General water of China Co., Ltd;3.Xiangtan Zhonghuan Water Affairs CO., Ltd;4.School of Environment, Tsinghua University
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| Abstract: |
| There is little research on the relationship between water supply prediction and water source /meteorological factors. Therefore, the daily water supply model of waterworks was established by analyzing the correlation between the hydrological information, water quality parameters and meteorological conditions of water source and daily water supply. After a waterworks automatic acquisition data analysis processing, the BP neural network model was used to predict the daily water supply of water plant. The prediction results are in good agreement with the actual situation, and the prediction error was little, basically meeting MEAP <5%, which can meet the actual demand of water supply system scheduling. It can be seen that the prediction neural network model is reasonable and provides a simple, feasible idea and method for daily water supply prediction of urban waterworks. |
| Key words: urban waterworks; daily water supply; BP neural network; prediction; MEAP |
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