An enhanced differential evolution based grey model for forecasting urban water consumption

被引：0

作者：

Wang, Weiwen ^{[1
]}

Jiang, Junyang ^{[1
]}

Fu, Minglei ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Coll Sci, Hangzhou 310023, Zhejiang, Peoples R China

来源：

2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年

关键词：

grey model; differential evolution algorithm; background value optimization; mean absolute percentage error;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：7643 / 7648

页数：6

共 18 条

[1] Optimal power flow using differential evolution algorithm
Abou El Ela, A. A.
Abido, M. A.
Spea, S. R.
[J]. ELECTRICAL ENGINEERING, 2009, 91 (02) : 69 - 78
[2] Forecasting electrical consumption by integration of Neural Network, time series and ANOVA
Azadeh, A.
Ghaderi, S. F.
Sohrabkhani, S.
[J]. APPLIED MATHEMATICS AND COMPUTATION, 2007, 186 (02) : 1753 - 1761
[3] Chang Hsuan T., 1999, IEEE INT C SYST MAN, V3, P309
[4] Identification time-delayed fractional order chaos with functional extrema model via differential evolution
Gao, Fei
Lee, Xue-jing
Fei, Feng-xia
Tong, Heng-qing
Deng, Yan-fang
Zhao, Hua-ling
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (04) : 1601 - 1608
[5] Forecasting the output of integrated circuit industry using a grey model improved by the Bayesian analysis
Hsu, Li-Chang
Wang, Chao-Hung
[J]. TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2007, 74 (06) : 843 - 853
[6] Kang J., 2012, Syst Eng Proc, V3, P85, DOI DOI 10.1016/J.SEPRO.2011.11.012
[7] Grey system theory-based models in time series prediction
Kayacan, Erdal
Ulutas, Baris
Kaynak, Okyay
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (02) : 1784 - 1789
[8] Lei Bao-dong, 2009, ENERGY FORECAST MODE, P1
[9] Using genetic algorithms and linear regression analysis for private housing demand forecast
Ng, S. Thomas
Skitmore, Martin
Wong, Keung Fai
[J]. BUILDING AND ENVIRONMENT, 2008, 43 (06) : 1171 - 1184
[10] Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model
Pao, Hsiao-Tien
Fu, Hsin-Chia
Tseng, Cheng-Lung
[J]. ENERGY, 2012, 40 (01) : 400 - 409

← 1 2 →