Flood susceptibility mapping in Brahmaputra floodplain of Bangladesh using deep boost, deep learning neural network, and artificial neural network

Autor:	Muhammad Al-Amin Hoque, Alireza Arabameri, Subodh Chandra Pal, Rabin Chakrabortty, Jesmin Jui, Naser Ahmed
Rok vydání:	2021
Předmět:	geography geography.geographical_feature_category Floodplain Flood myth Artificial neural network Computer science business.industry Deep learning Geography Planning and Development Natural (archaeology) Artificial intelligence Water resource management business Water Science and Technology
Zdroj:	Geocarto International. 37:8770-8791
ISSN:	1752-0762 1010-6049
DOI:	10.1080/10106049.2021.2005698
Popis:	Floods are considered one of the most destructive natural hydro-meteorological disasters across the world. The present study attempts to assess flood susceptibility of the Brahmaputra floodplain of...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cd59a54a46d539ce0989779a59dfc442 https://doi.org/10.1080/10106049.2021.2005698 Zobrazit plný text záznamu