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How to cite: UNEŞ, F., DEMİRCİ, M., VARÇİN, H. (2020) Estimation of Dam Reservoir Volume Using Neural Networks. 2020 ”Air and Water – Components of the Environment” Conference Proceedings, Cluj-Napoca, Romania, p. 191-200,
DOI: 10.24193/AWC2020_18.

2020 Content

 

 

ESTIMATION OF DAM RESERVOIR VOLUME USING NEURAL NETWORKS

Fatih UNEŞ, Mustafa DEMİRCİ, Hakan VARÇİN
 

DOI: 10.24193/AWC2020_18

ABSTRACT. – Dam reservoir capacity estimations are important for operation, design and safety assessments of dam structures. In this study, the reservoir capacity of the Stony Brook dam in US state of Massachusetts was tried to be estimated with data taken from US Geological Survey Institute (USGS). Reservoir capacity was estimated by using two types Neural Networks, namely, Artificial Neural Networks (ANN), Generalized Neural Networks (GRNN), and also Multi Linear Regression method (MLR) models. The model results were compared with measurements by calculating Mean Square Error (MSE), Mean Absolute Error (MAE), correlation coefficient statistics.
 

Keywords: Estimation, Artificial Neural Networks, Reservoir, Multiple Linear Regression

Creative Commons Attribution Non-Commercial 3.0 License.

 

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