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Preliminary communication

https://doi.org/10.14256/JCE.2316.2018

Prediction of maximum annual flood discharges using artificial neural network approaches

Tugce Anilan
Sinan Nacar
Murat Kankal
Omer Yuksek


Full text: croatian pdf 354 Kb

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Full text: english pdf 340 Kb

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Abstract

The applicability of artificial neural network (ANN) approaches for estimation of maximum annual flows is investigated in the paper. The performance of three neural network models is compared: multi layer perceptron neural networks (MLP_NN), generalized feed forward neural networks (GFF_NN), and principal component analysis with neural networks (PCA_NN). The proposed approaches were applied to 33 stream-gauging stations. It was found that the optimal 3-hidden layered PCA_NN method was more appropriate than the optimal MLP_NN and GFF_NN models for the estimation of maximum annual flows.

Keywords

artificial neural networks; principal component analysis; maximum annual flows

Hrčak ID:

237381

URI

https://hrcak.srce.hr/237381

Publication date:

20.4.2020.

Article data in other languages: croatian

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