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.
Original language | English |
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Pages (from-to) | 1152-1161 |
Number of pages | 10 |
Journal | Lecture Notes in Computer Science |
Volume | 3612 |
Issue number | PART III |
Publication status | Published - 24 Oct 2005 |
Event | First International Conference on Natural Computation, ICNC 2005 - Changsha, China Duration: 27 Aug 2005 → 29 Aug 2005 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science