Application of artificial neural networks for hydrological modelling in karst
Апстракт
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.
Кључне речи:
artificial neural network / SVR / ANFIS / rainfall-runoff ratio in karst areasИзвор:
Građevinar, 2018, 70, 1, 1-10Издавач:
- Union of Croatian Civil Engineers and Technicians
DOI: 10.14256/JCE.1594.2016
ISSN: 0350-2465
WoS: 000427672000001
Scopus: 2-s2.0-85042587602
Колекције
Институција/група
GraFarTY - JOUR AU - Kovacević, Miljan AU - Ivanišević, Nenad AU - Dašić, Tina AU - Marković, Ljubo PY - 2018 UR - https://grafar.grf.bg.ac.rs/handle/123456789/968 AB - 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. PB - Union of Croatian Civil Engineers and Technicians T2 - Građevinar T1 - Application of artificial neural networks for hydrological modelling in karst EP - 10 IS - 1 SP - 1 VL - 70 DO - 10.14256/JCE.1594.2016 ER -
@article{ author = "Kovacević, Miljan and Ivanišević, Nenad and Dašić, Tina and Marković, Ljubo", year = "2018", 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.", publisher = "Union of Croatian Civil Engineers and Technicians", journal = "Građevinar", title = "Application of artificial neural networks for hydrological modelling in karst", pages = "10-1", number = "1", volume = "70", doi = "10.14256/JCE.1594.2016" }
Kovacević, M., Ivanišević, N., Dašić, T.,& Marković, L.. (2018). Application of artificial neural networks for hydrological modelling in karst. in Građevinar Union of Croatian Civil Engineers and Technicians., 70(1), 1-10. https://doi.org/10.14256/JCE.1594.2016
Kovacević M, Ivanišević N, Dašić T, Marković L. Application of artificial neural networks for hydrological modelling in karst. in Građevinar. 2018;70(1):1-10. doi:10.14256/JCE.1594.2016 .
Kovacević, Miljan, Ivanišević, Nenad, Dašić, Tina, Marković, Ljubo, "Application of artificial neural networks for hydrological modelling in karst" in Građevinar, 70, no. 1 (2018):1-10, https://doi.org/10.14256/JCE.1594.2016 . .