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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 |
Issue Date: | 2005 | 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 | 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. | Keywords: | Adaptive systems Hydropower reservoirs Forecasting reservoir inflow Algorithms Membership functions Reservoirs (water) Manwan Hydropower |
Publisher: | Springer | 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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LNCS9.pdf | Pre-published version | 199.28 kB | Adobe PDF | View/Open |
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