Feed Forward Neural Network Modeling for Rainfall Prediction

Yasin Hasbi; Warsito Budi; Santoso Rukun

doi:10.1051/e3sconf/20187305017

All issues

Volume 73 (2018)

E3S Web Conf., 73 (2018) 05017

References

Open Access

Issue		E3S Web Conf. Volume 73, 2018 The 3^rd International Conference on Energy, Environmental and Information System (ICENIS 2018)


Article Number		05017
Number of page(s)		5
Section		Environmental Technology and Pollution Control
DOI		https://doi.org/10.1051/e3sconf/20187305017
Published online		21 December 2018

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Kim, S., Seo, Y., and Lee, C.J., 2016, Modeling of Rainfall by Combining Neural Computation and Wavelet Technique, Procedia Engineering, 154: pp 1231–1236 [CrossRef] [Google Scholar]
Lin, G.F dan Wu, M.C., 2009, A hybrid neural network model for typhoon-rainfall forecasting, Journal of Hydrology 375 (2009) 450–458 (SOM &MLP) [CrossRef] [Google Scholar]
Mekanik, F., Imteaz, M.A., Trinidad, S.G., Elmahdi, A., 2013, Multiple Regression and Artificial Neural Network for Long-Term Rainfall Forecasting Using Large Scale Climate Modes, Journal of Hydrology 503 (2013) 11–21 [CrossRef] [Google Scholar]
Wang, Y.M. and Traore, S., 2009, Time-lagged recurrent network for forecasting episodic event suspended sediment load in typhoon prone area, International Journal of Physical Sciences Vol. 4 (9), pp. 519–528, Available online at http://www.academiciournals.org/ijps [Google Scholar]
Yasin, H., 2014, Prediction of Weekly Rainfall in Semarang City use Support Vector Regressions, Prosiding Seminar Internasional the 4th ISNPINSA, Hotel Patra Jasa Semarang [Google Scholar]
Yasin, H. dan Prahutama, A., 2015, Prediction of Weekly Rainfall in Semarang City Use Support Vector Regression (SVR) with Quadratic Loss Function, International Journal of Science and Engineering (IJSE), ISSN: 1086-5023, Vol. 9 No.1 [Google Scholar]

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[1] Asadi, S., Shahrabi, J., Abbaszadeh, P., Tabanmehr, S., 2013, A new hybrid artificial neural networks for rainfall-runoff process modeling, Neurocomputing, 121, pp 470–480 [CrossRef] [Google Scholar]

[2] Benmahdjouba, K., Ameura, Z., Boulifa, M., 2013, Forecasting of Rainfall using Time Delay Neural Network in Tizi-Ouzou (Algeria), Energy Procedia 36 (2013) 1138–1146 [CrossRef] [Google Scholar]

[3] Cigizoglu, H.,K., Askin., P., Ozturk, A., Gurbuz, A., Ayhan, O., Yildiz, Mand Ucar, I., 2008, Artificial Neural Network Models in Rainfall-Runoff Modelling of Turkish Rivers, International Congress on River Basin Management, pp. 560–571 [Google Scholar]

[4] Kim, S., Seo, Y., and Lee, C.J., 2016, Modeling of Rainfall by Combining Neural Computation and Wavelet Technique, Procedia Engineering, 154: pp 1231–1236 [CrossRef] [Google Scholar]

[5] Lin, G.F dan Wu, M.C., 2009, A hybrid neural network model for typhoon-rainfall forecasting, Journal of Hydrology 375 (2009) 450–458 (SOM &MLP) [CrossRef] [Google Scholar]

[6] Mekanik, F., Imteaz, M.A., Trinidad, S.G., Elmahdi, A., 2013, Multiple Regression and Artificial Neural Network for Long-Term Rainfall Forecasting Using Large Scale Climate Modes, Journal of Hydrology 503 (2013) 11–21 [CrossRef] [Google Scholar]

[7] Wang, Y.M. and Traore, S., 2009, Time-lagged recurrent network for forecasting episodic event suspended sediment load in typhoon prone area, International Journal of Physical Sciences Vol. 4 (9), pp. 519–528, Available online at http://www.academiciournals.org/ijps [Google Scholar]

[8] Yasin, H., 2014, Prediction of Weekly Rainfall in Semarang City use Support Vector Regressions, Prosiding Seminar Internasional the 4th ISNPINSA, Hotel Patra Jasa Semarang [Google Scholar]

[9] Yasin, H. dan Prahutama, A., 2015, Prediction of Weekly Rainfall in Semarang City Use Support Vector Regression (SVR) with Quadratic Loss Function, International Journal of Science and Engineering (IJSE), ISSN: 1086-5023, Vol. 9 No.1 [Google Scholar]