摘要
根据城市用水量的影响因素及特点,基于BP神经网络,建立了一种综合多元分析特点和时间序 列分析的动态水量预测模型.经沈阳市实例验证,该模型预测误差小,可满足供水系统调度的实际需要.
Based on BP model of the artificial neural network, according to the factors and features of urban water supply, a dynamic water consumption forecasting model with the characteristics of both regression and time series is developed. Experiments at Shenyang City show that the forecasting error of the model is small and the model can meet the practical requirement of water-supply dispatch system.
出处
《信息与控制》
CSCD
北大核心
2004年第3期364-368,共5页
Information and Control
基金
国家自然科学基金资助项目(70171056)
关键词
城市供水
用水量预测
人工神经元网络
BP算法
urban water supply
water consumption forecast
artificial neural network
BP algorithm
