Title :
The Combination Forecasting Model for Urban Water Consumption Based on Support Vector Machines
Author :
Sun, Wei ; Yan, Xingxing ; Li, Yanhong
Author_Institution :
North China Electr. Power Univ., Baoding
Abstract :
During the optimal control in city water supply, the short-term urban water consumption prediction is gist. This paper establish a new model of the short-term urban water consumption prediction - the combination forecasting model based on support vector machines (CFSVM), with Chinese city´s water consumption as samples. After rectifying the model, it gets higher predicting precision. Comparing to other warning models, the CFSVM model for Chinese urban water consumption prediction really has bigger application foreground because of its better characters such as higher accuracy rate.
Keywords :
forecasting theory; optimal control; set theory; support vector machines; water supply; Chinese urban water consumption; city water supply; combination forecasting model based on support vector machines; optimal control; Cities and towns; Information technology; Optimal control; Prediction methods; Predictive models; Random number generation; Support vector machines; Technology forecasting; Urban areas; Water resources; BP; Combination Forecast; SVM; Urban Water Consumption;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.233