Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1279
Title: Long-term prediction of discharges in Manwan Hydropower using adaptive-network-based fuzzy inference systems models
Authors: Cheng, C
Lin, J
Sun, Y
Chau, KW 
Keywords: Adaptive systems
Hydropower reservoirs
Forecasting reservoir inflow
Algorithms
Membership functions
Reservoirs (water)
Manwan Hydropower
Issue Date: 2005
Publisher: Springer
Source: In L Wang, K Chen & YS Ong (Eds.), Advances in natural computation : first international conference, ICNC 2005, Changsha, China, August 27-29, 2005 : proceedings, p. 1152-1161. Berlin ; New York: Springer, 2005 How to cite?
Series/Report no.: Lecture notes in computer science ; v. 3162
Abstract: Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flows associated with ANFIS model are tested. When compared to the ANN model, the ANFIS model has shown a significant forecast improvement. The training and validation results show that the ANFIS model is an effective algorithm to forecast the long-term discharges in Manwan Hydropower. The ANFIS model is finally employed in the advanced water resource project of Yunnan Power Group.
URI: http://hdl.handle.net/10397/1279
ISBN: 978-3-540-28320-1
DOI: 10.1007/11539902_145
Rights: © Springer-Verlag Berlin Heidelberg 2005. The original publication is available at http://www.springerlink.com.
Appears in Collections:Book Chapter

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