Application of artificial neural networks for hydrological modelling in Karst

Author

Miljan Kovačević
Nenad Ivanišević
Tina Dašić
Ljubo Marković

Files

Publication Date

10-2-2018

Publication Title

Gradevinar

Volume Number

70

Issue Number

1

Abstract

The possibility of short-term water flow forecasting in a karst region is presented in this paper. Four state-of-the-art machine learning algorithms are used for the one day ahead forecasting: multi-layer perceptron neural network, radial basis function neural network, support vector machines for regression (SVR), and adaptive neuro fuzzy inference system (ANFIS). The results show that the ANFIS model outperforms other algorithms when the root mean square error and mean absolute error are used as quality indicators.

Keywords

Artificial neural networks, SVR, Rainfall runoff, Karst

Document Type

Article

Digital Object Identifier (DOI)

https://doi.org/10.14256/JCE.1594.2016

Language

English; Croation

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Kovačević, Miljan; Ivanišević, Nenad; Dašić, Tina; and Marković, Ljubo, "Application of artificial neural networks for hydrological modelling in Karst" (2018). KIP Articles. 8279.
https://digitalcommons.usf.edu/kip_articles/8279