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Prethodno priopćenje

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


Puni tekst: hrvatski pdf 354 Kb

str. 215-224

preuzimanja: 341

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Puni tekst: engleski pdf 340 Kb

str. 215-224

preuzimanja: 354

citiraj


Sažetak

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.

Ključne riječi

artificial neural networks; principal component analysis; maximum annual flows

Hrčak ID:

237381

URI

https://hrcak.srce.hr/237381

Datum izdavanja:

20.4.2020.

Podaci na drugim jezicima: hrvatski

Posjeta: 1.804 *