Fuzzy Neural Network Modeling of Reservoir Operation

被引:27
|
作者
Deka, Paresh Chandra [1 ]
Chandramouli, V. [2 ,3 ]
机构
[1] ArbaMinch Univ, Arbaminch, Ethiopia
[2] Univ Kentucky, Dept Civil Engn, Kentucky Water Resources Res Ctr, Lexington, KY 40506 USA
[3] Univ Kentucky, Dept Civil Engn, Adjunct Fac, Lexington, KY 40506 USA
关键词
INTELLIGENT CONTROL; PREDICTION; SYSTEM;
D O I
10.1061/(ASCE)0733-9496(2009)135:1(5)
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The present study aims at the application of the hybrid model, which consists of artificial neural network and fuzzy logic in the reservoir operating policy during critical periods. The proposed hybrid model [fuzzy neural network (FNN)] combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The FNN model is found to be highly adaptive and efficient in investigating nonlinear relationships among different variables. The FNN model has been developed to study the behavior of optimal release operating policy on the proposed reservoir in Pagladiya River of the Assam State in India. Here, reservoir operation policies were formulated through dynamic programming. The optimal release was related to storage, inflow, and demand. The advantages of using the FNN model in reservoir release are discussed using the case study.
引用
收藏
页码:5 / 12
页数:8
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