Prediction of Millers Ferry Dam Reservoir Level in USA Using Artificial Neural Network
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Dosyalar
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Budapest Univ Technology Economics
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Reservoir level modeling is important for the operation of dam reservoir, design of hydraulic structures, determining pollution in reservoir and the safety of dam. In this study, daily reservoir levels for Millers Ferry Dam on the Alabama River in USA were predicted using artificial neural networks (ANN). Bayesian regularization backpropagation training algorithm is employed for optimization of the network. The results of the optimal ANN models were compared with conventional auto-regressive models (AR), auto-regressive moving average (ARMA), multi-linear regression (MLR) models. The models are compared with each other according to the three criteria, namely, mean square errors, mean absolute relative error and correlation coefficient. The comparison results show that the ANN models perform better than the conventional models.
Açıklama
Anahtar Kelimeler
Reservoir level, prediction, artificial neural network, auto-regressive moving average
Kaynak
Periodica Polytechnica-Civil Engineering
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
59
Sayı
3
