A review of deep learning and machine learning techniques for hydrological inflow forecasting

SD Latif, AN Ahmed - Environment, Development and Sustainability, 2023 - Springer
Conventional machine learning models have been widely used for reservoir inflow and
rainfall prediction. Nowadays, researchers focus on a new computing architecture in the …

[HTML][HTML] Application of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo River Basin, Ethiopia

H Tamiru, MO Dinka - Journal of Hydrology: Regional Studies, 2021 - Elsevier
Abstract Study region Lower Baro River, Ethiopia. Study focus This paper presents the
novelty of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo …

Review of wavelet denoising algorithms

A Halidou, Y Mohamadou, AAA Ari… - Multimedia Tools and …, 2023 - Springer
Although there has been a lot of progress in the general area of signal denoising, noise
removal remains a very challenging problem in real-world communication systems …

Generalizing rapid flood predictions to unseen urban catchments with conditional generative adversarial networks

CAF do Lago, MH Giacomoni, R Bentivoglio… - Journal of …, 2023 - Elsevier
Two-dimensional hydrodynamic models are computationally expensive. This drawback can
limit their application to solving problems requiring real-time predictions or several …

Medium-long-term prediction of water level based on an improved spatio-temporal attention mechanism for long short-term memory networks

Y Wang, Y Huang, M Xiao, S Zhou, B Xiong, Z Jin - Journal of Hydrology, 2023 - Elsevier
River water level usually given by nonlinear and nonstationary time series and affected by
numerous complex spatial and temporal factors. But not all input factors are positively …

[HTML][HTML] Ensemble neural networks for the development of storm surge flood modeling: A comprehensive review

SK Nezhad, M Barooni, D Velioglu Sogut… - Journal of Marine …, 2023 - mdpi.com
This review paper focuses on the use of ensemble neural networks (ENN) in the
development of storm surge flood models. Storm surges are a major concern in coastal …

[HTML][HTML] Enhancing community resilience in arid regions: A smart framework for flash flood risk assessment

M Nakhaei, P Nakhaei, M Gheibi, B Chahkandi… - Ecological …, 2023 - Elsevier
This paper presents a novel framework for smart integrated risk management in arid regions.
The framework combines flash flood modelling, statistical methods, artificial intelligence (AI) …

[HTML][HTML] A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon

FY Dtissibe, AAA Ari, H Abboubakar, AN Njoya… - Scientific African, 2024 - Elsevier
Flood crises are the consequence of climate change and global warming, which lead to an
increase in the frequency and intensity of heavy rainfall. Floods are, and remain, natural …

Flood susceptibility modeling of the Karnali river basin of Nepal using different machine learning approaches

S Duwal, D Liu, PM Pradhan - Geomatics, Natural Hazards and …, 2023 - Taylor & Francis
Abstract The Karnali River Basin (KRB) comprises the longest river in Nepal, located south
of the Himalayas. Despite its high susceptibility to floods, the basin lacks detailed studies …

Potential use of artificial intelligence (AI) in disaster risk and emergency health management: a critical appraisal on environmental health

LF Bari, I Ahmed, R Ahamed, TA Zihan… - Environmental …, 2023 - journals.sagepub.com
The risk evaluation of natural disasters is an obstacle to ensuring healthcare services during
catastrophic events worldwide. Therefore, timely and appropriate environmental health risk …