Predicting and analyzing flood susceptibility using boosting-based ensemble machine learning algorithms with SHapley Additive exPlanations

Autor:	Halit Enes Aydin, Muzaffer Can Iban
Rok vydání:	2022
Předmět:	Atmospheric Science Earth and Planetary Sciences (miscellaneous) Water Science and Technology
Zdroj:	Natural Hazards. 116:2957-2991
ISSN:	1573-0840 0921-030X
DOI:	10.1007/s11069-022-05793-y
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::50c25bc3e4dfde5b44d0785636373635 https://doi.org/10.1007/s11069-022-05793-y Zobrazit plný text záznamu Full text from SpringerLink