An enhanced differential evolution based grey model for forecasting urban water consumption
Forecasting water consumption plays a great important role in water resource utilization and management.Grey model(GM)with differential evolution(DE)algorithm has obtained much great success in practical forecasting applications,especially for the forecasting problems with little historical information.In this paper,an enhanced DE based GM which named Step-DE-GM is proposed to forecast urban water consumption.Simulation results show that Step-DE-GM(1,1)can reduce the value of mean absolute percentage error(MAPE)by 0.764%and 0.733%compared with GM(1,1)and DE-GM(1,1),which means Step-DE-GM achieves higher prediction accuracy.
grey model differential evolution algorithm background value optimization mean absolute percentage error
Weiwen Wang Junyang Jiang Minglei Fu
College of Science,Zhejiang University of Technology,Hangzhou,China,310023
国际会议
The 33th Chinese Control Conference第33届中国控制会议
南京
英文
7643-7648
2014-07-28（万方平台首次上网日期，不代表论文的发表时间）