DAM RESERVOIR LEVEL MODELING BY NEURAL NETWORK APPROACH: A CASE STUDY
Yükleniyor...
Tarih
2010
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Acad Sciences Czech Republic, Inst Computer Science
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Prediction of reservoir level fluctuation is important in the operation, design, and security of dams. In this paper, Artificial Neural Networks (ANN) is used for modeling. In such modeling approaches, it is possible to determine darn reservoir level and water balance (budget) by taking the monthly average precipitation and needed parameters into consideration. The basic data are available for over 29 years at the Tahtakopru Dam in the southeast Mediterranean region of Turkey. As a sub-approach of ANN, a multi layer perceptron (MLP) is used. Bayesian regularization back-propagation training algorithm is employed for optimization of the network. MLP results are compared with the results of conventional multiple linear regression (MLR) and autoregressive (AR) models. The comparison shows that the ANN model provides better performance than the mentioned models in reservoir level estimation.
Açıklama
Anahtar Kelimeler
Artificial Neural Networks (ANNs), dam, reservoir level, prediction, multi layer perceptron, model
Kaynak
Neural Network World
WoS Q DeÄŸeri
Q4
Scopus Q DeÄŸeri
Cilt
20
Sayı
4
