基于神经网络的南京市用水量预测  

Prediction of Nanjing Water Consumption Based on Neural Network

作　　者：王浏琳 陈家栋[3] 张方敏[1,2] WANG Liu-lin;CHEN Jia-dong;ZHANG Fang-min(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,College of Applied Meteorology,Nanjing University of Information Science&Technology,Nanjing 210044,China;Jiangsu Key Laboratory of Agricultural Meteorology,College of Applied Meteorology,Nanjing University of Information Science&Technology,Nanjing 210044,China;Nanjing Branch of Jiangsu Hydrological and Water Resources Survey Bureau,Nanjing 210008,China)

机构地区：[1]南京信息工程大学气象灾害预报预警与评估协同创新中心,江苏南京210044 [2]南京信息工程大学应用气象学院江苏省农业气象重点实验室,江苏南京210044 [3]江苏省水文水资源勘测局南京分局,江苏南京210008

出　　处：《水电能源科学》2023年第12期28-31,共4页Water Resources and Power

基　　金：国家重点研发计划(2018YFC1506606);江苏省碳达峰碳中和科技创新专项资金项目(BK20220017)。

摘　　要：分析南京市用水量现状,合理预测南京市用水量,掌握未来用水需求,对南京市水资源的长远规划和配置具有重大意义。对南京市2009~2019年用水量分析表明,工业、农业用水在南京市总用水量中比重较大,对总用水量的变化起着至关重要的作用。其次,采用灰色预测GM(1,1)模型与Elman神经网络的组合模型预测南京市各区及全市总用水量。结果表明,灰色Elman神经网络模型对2009~2019年南京市全市总用水量的预测效果良好,预测的相对误差均小于3.5%,预测结果的多年平均相对误差为1.55%;在南京市2019年各区用水量预测中,预测结果的相对误差均小于8.5%,效果较好。可见所用模型能准确地预测南京市用水量,对有效控制区域用水量,实现“四水四定”原则具有重要意义。It is of great significance for the long-term planning and allocation of Nanjing water resources to analyze the current situation of Nanjing water consumption,make reasonable prediction of Nanjing water consumption and master the future water demand.The analysis of water consumption in Nanjing from 2009 to 2019 showed that industrial and agricultural water consumption accounted for a large proportion of total water consumption in Nanjing,which played a crucial role in the change of total water consumption.The combined model of grey GM(1,1)model and Elman neural network was used to forecast the water consumption of all districts and the total water consumption of Nanjing.The results show that the grey Elman neural network model has a good prediction effect on the total water consumption of Nanjing City from 2009 to 2019.The relative errors of the forecasts were all less than 3.5%,and the average relative errors of the predicted results over the years were 1.55%;The relative error of the forecast results is less than 8.5%in the forecast of the water consumption of all districts in Nanjing in 2019.The model used in this paper can accurately predict the water consumption of Nanjing,which is of great significance to effectively control the regional water consumption and realize the principle of"four water and four determinations".

关 键 词：机器学习 灰色Elman神经网络 组合模型 用水量预测 

分 类 号：TV213.4[水利工程—水文学及水资源]