Implication of novel hybrid machine learning model for flood subsidence susceptibility mapping: A representative case study in Saudi Arabia
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Published:2024-02
Issue:
Volume:630
Page:130692
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ISSN:0022-1694
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Container-title:Journal of Hydrology
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language:en
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Short-container-title:Journal of Hydrology
Author:
Al-Areeq Ahmed M.ORCID, Saleh Radhwan A.A.ORCID, Ghaleb Mustafa, Abba Sani I.ORCID, Yaseen Zaher Mundher
Reference101 articles.
1. Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees;Abedi;Geocarto Int.,2022 2. Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study;Al-Abadi;Arab. J. Geosci.,2018 3. Al-Aizari, A.R., Al-Masnay, Y.A., Aydda, A., Zhang, J., Ullah, K., Islam, A.R.M.T., Habib, T., Kaku, D.U., Nizeyimana, J.C., Al-Shaibah, B., Khalil, Y.M., AL-Hameedi, W.M.M., Liu, X., 2022. Assessment Analysis of Flood Susceptibility in Tropical Desert Area: A Case Study of Yemen. Remote Sens. 2022, vol. 14, Page 4050 14, 4050. 10.3390/RS14164050. 4. Flash flood susceptibility assessment using the parameters of drainage basin morphometry in SE Bangladesh;Alam;Quat. Int.,2021 5. Alam, Z., Sun, L., Zhang, C., Su, Z., Samali, B., 2020. Experimental and numerical investigation on the complex behaviour of the localised seismic response in a multi-storey plan-asymmetric structure. 17, 86–102. 10.1080/15732479.2020.1730914.
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