A reliable hybrid outlier robust non-tuned rapid machine learning model for multi-step ahead flood forecasting in Quebec, Canada-Reference-Cited by-同舟云学术

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A reliable hybrid outlier robust non-tuned rapid machine learning model for multi-step ahead flood forecasting in Quebec, Canada

Published:2022-11 Issue: Volume:614 Page:128592
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Ebtehaj Isa,Bonakdari Hossein

Funder

Natural Sciences and Engineering Research Council of Canada

Fonds Québécois de la Recherche sur la Nature et les Technologies

Fonds de recherche du Québec – Nature et technologies

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference96 articles.

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2. Alexander, A.A., Thampi, S.G., NR, C., 2018. Development of hybrid wavelet-ANN model for hourly flood stage forecasting. ISH J. Hydraul. Eng. 24(2), 266-274. doi:10.1080/09715010.2017.1422192.

3. Al-Fawa’Reh, M., Hawamdeh, A., Alrawashdeh, R., Jafar, M.T., 2021. Intelligent Methods for flood forecasting in Wadi al Wala, Jordan. in: 2021 Int. Cong. Adv. Technol. Eng. (ICOTEN) IEEE, pp. 1-9.

4. Prediction of daily rainfall by a hybrid wavelet-season-neuro technique;Altunkaynak;J. Hydrol.,2015

5. The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network;Bartlett;IEEE T Inform. Theory,1998

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