Flood hazard mapping methods: A review
Flood hazard mapping (FHM) has undergone significant development in terms of approach
and capacity of the result to meet the target of policymakers for accurate prediction and …
and capacity of the result to meet the target of policymakers for accurate prediction and …
A comprehensive review of deep learning applications in hydrology and water resources
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume,
variety and velocity of water-related data are increasing due to large-scale sensor networks …
variety and velocity of water-related data are increasing due to large-scale sensor networks …
Review and empirical analysis of sparrow search algorithm
Y Yue, L Cao, D Lu, Z Hu, M Xu, S Wang, B Li… - Artificial Intelligence …, 2023 - Springer
In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
ARMT Islam, S Talukdar, S Mahato, S Kundu… - Geoscience …, 2021 - Elsevier
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection
The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …
combinatorial optimization problem, which effectively combines the memetic algorithm …
[HTML][HTML] Predicting flood susceptibility using LSTM neural networks
Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …
makers to prevent and manage disasters. Plenty of studies have used machine learning …
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
Flood risk assessment is an important task for disaster management activities in flood-prone
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
The flooding in Bangladesh during monsoon season is very common and frequently
happens. Consequently, people have been experiencing tremendous damage to properties …
happens. Consequently, people have been experiencing tremendous damage to properties …
Estimating daily reference evapotranspiration based on limited meteorological data using deep learning and classical machine learning methods
Z Chen, Z Zhu, H Jiang, S Sun - Journal of Hydrology, 2020 - Elsevier
To evaluate the performance of deep learning methods (DL) for reference
evapotranspiration estimation and to assess the applicability of the developed DL models …
evapotranspiration estimation and to assess the applicability of the developed DL models …
Comparative study of landslide susceptibility mapping with different recurrent neural networks
This paper aims to use recurrent neural networks (RNNs) to perform landslide susceptibility
mapping in Yongxin County, China. The two main contributions of this study are summarized …
mapping in Yongxin County, China. The two main contributions of this study are summarized …