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Ensemble Machine Learning for Urban Flood Hazard Assessment:

, In: 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI),

Taromideh, Fereshteh ; Fazloula, Ramin ; Choubin, Bahram.. - p. 000525-000530 , 2024

Link: https://doi.org/10.1109/SAMI60510.2024.10432902

RT 
T1 <cTitle>2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)</cTitle>: T1 <Title>Ensemble Machine Learning for Urban Flood Hazard Assessment</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10432902&Exemplar=1&LAN=DE
				
A1 Taromideh, Fereshteh
A1 Fazloula, Ramin
A1 Choubin, Bahram
A1 Masoodi, Mehdi
A1 Mosavi, Amir
YR 2024
SN 2767-9438
K1 Radio frequency
K1 Urban areas
K1 Predictive models
K1 Floods
K1 Ensemble learning
K1 Random forests
K1 Regression tree analysis
K1 ensemble learning
K1 machine learning
K1 natural hazard
K1 urban flood
K1 ensemble model
K1 deep learning
K1 artificial intelligence
K1 AI
K1 big data
K1 data science
K1 soft computing
K1 applied mathematics
K1 hydrology
K1 hydrological model
K1 ensemble machine learning
K1 XAI
K1 explainable machine learning
K1 susceptibility mapping
SP 000525
OP 000530
LK http://dx.doi.org/https://doi.org/10.1109/SAMI60510.2024.10432902
DO https://doi.org/10.1109/SAMI60510.2024.10432902
SF ELIB - SuUB Bremen

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