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Calibration and verification of QUAL2E for the reaeration coefficient using genetic algorithms
Date
2004-06-11
Author
Göktaş, Recep Kaya
Aksoy, Ayşegül
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https://hdl.handle.net/11511/87769
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Calibration and verification of QUAL2E using Genetic algorithm optimization
GÖKTAŞ, Recep Kaya; Aksoy, Ayşegül (American Society of Civil Engineers (ASCE), 2007-03-01)
In this study, the QUAL2E model is linked with a genetic algorithm (GA) in order to conduct the calibration and verification of the model. The efficacy of the optimization model was tested for different observation data quality represented by the perfect and noisy data assumptions. Four cases were studied. In the first (base) case, calibration was conducted for the reach-variable reaeration coefficient (K2) and the sediment oxygen demand rate (K4). In the second case, the number of sampling points was incre...
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In recent years, Artificial Neural Networks (ANN) have become widely popular tools in various disciplines of engineering, including civil engineering. In this thesis, Multi-layer perceptron with back-propagation type of network is utilized in calibration of the finite element model of a long span cantilever through truss called Commodore Barry Bridge (CBB). The essence of calibration lies in the phenomena of comparing and correlating the structural response of an analytical model with experimental results a...
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R. K. Göktaş and A. Aksoy, “Calibration and verification of QUAL2E for the reaeration coefficient using genetic algorithms,” İzmir, Türkiye, 2004, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/87769.