DocumentCode
507249
Title
Research on Forecasting Method of Urban Water Demand Based on Fuzzy Theory
Author
Liu, Hongbo ; Deng, Tegang ; Zhang, Hongwei
Author_Institution
Sch. of Environ. Sci. & Technol., Tianjin Univ., Tianjin, China
Volume
6
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
389
Lastpage
395
Abstract
Water demand forecasting is very important in urban water supply management. A large number of researches have been done on water demand forecasting methods. In order to meet the easy operation and high accuracy requirements, a new forecasting method based on fuzzy theory, adaptive neuro-fuzzy inference system (ANFIS), was presented. The parameters of this method are obtained by the original fuzzy rules from the samples and optimized according to the latest history data based on adaptive mix learning arithmetic. At the same time, this forecasting system input variables are embodied the information, such as factors of burthen increasing, periodicity, the load changeable trends and the weather etc. The system configuration is very simple and valid. Based on imitated example, the consequence predicting precision of this method can satisfy the engineering request.
Keywords
adaptive systems; demand forecasting; environmental management; fuzzy reasoning; fuzzy set theory; water resources; adaptive mix learning arithmetic; adaptive neuro-fuzzy inference system; fuzzy theory; urban water supply management; water demand forecasting; water demand forecasting method; Adaptive systems; Artificial neural networks; Autoregressive processes; Biological neural networks; Demand forecasting; Economic forecasting; Fuzzy systems; Partial response channels; Predictive models; Water resources; adaptive neuro-fuzzy inference system; fuzzy inference; fuzzy theory; water demand forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.639
Filename
5359875
Link To Document