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Published: Građevinar 70 (2018) 1
Paper type: Preliminary report
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Application of artificial neural networks for hydrological modelling in Karst

Miljan Kovačević, Nenad Ivanišević, Tina Dašić, Ljubo Marković

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, ANFIS, rainfall-runoff ratio in karst areas

HOW TO CITE THIS ARTICLE:

Kovačević, M., Ivanišević, N., Dašić, T., Marković, L.: Application of artificial neural networks for hydrological modelling in Karst, GRAĐEVINAR, 70 (2018) 1, pp. 1-10, doi: https://doi.org/10.14256/JCE.1594.2016

OR:

Kovačević, M., Ivanišević, N., Dašić, T., Marković, L. (2018). Application of artificial neural networks for hydrological modelling in Karst, GRAĐEVINAR, 70 (1), 1-10, doi: https://doi.org/10.14256/JCE.1594.2016

LICENCE:

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This paper is licensed under a Creative Commons Attribution 4.0 International License.
Authors:
Miljan Kovacevic
Miljan Kovačević
Ivanisevic Nenad WEB
Nenad Ivanišević
University of Belgrade
Faculty of Civil Engineering
Foto Tina Dasic WEB
Tina Dašić
University of Belgrade
Faculty of Civil Engineering
Ljubo Markovic slika
Ljubo Marković
Facufty of Technical Sciences
Kosovska Mitrovica