摘要
为了减少二次供水设施给小区供水管网所带来的压力,对供水管网运行状况进行更加精确的预测。结合物联网和时间序列分析等技术,通过对供水管网的历史数据的分析,采用季节性ARIMA模型对供水数据进行预测。设计数据预测分析的步骤和方案,建立方差估值为0.404 9、AIC为284.85的ARIMA(3,0,1)×(1,1,1)24模型。实验结果表明,设计的季节性ARIMA模型的预测周期短且有较高的预测精度,能够有效地对供水管网运行状态进行预测。
In order to reduce the pressure on the secondary water supply facilities to the regional water supply network, we need to accurately predict the operation of the water supply network. By using the technology of the Internet of Things and time series, and through the analysis of the historical data of water supply network, a seasonal ARIMA model is used to predict the data. The data analysis steps and programs were designed, and the ARIMA（3,0,1 ） × （1, 1,1 ） 24 model with estimated variance of 0. 404 9 and AIC of 284.85 was established. The experimental results show that the seasonal ARIMA model has a short prediction period and a high prediction measuring accuracy, which can effectively predict the operation of water supply network.
出处
《计算机应用与软件》
北大核心
2018年第1期118-122,294,共6页
Computer Applications and Software
基金
江苏省重点研发计划项目(BE2015189)
