By Topic

Research on Forecasting Method of Urban Water Demand Based on Fuzzy Theory

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hongbo Liu ; Sch. of Environ. Sci. & Technol., Tianjin Univ., Tianjin, China ; Tegang Deng ; Hongwei Zhang

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.

Published in:

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on  (Volume:6 )

Date of Conference:

14-16 Aug. 2009