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A novel machine learning tool for current and future flood susceptibility map** by integrating remote sensing and geographic information systems
A Amiri, K Soltani, I Ebtehaj, H Bonakdari - Journal of Hydrology, 2024 - Elsevier
Flood map** is essential for managing and mitigating the risks associated with flood
events. This study integrates weighted overlay analysis and analytical network process to …
events. This study integrates weighted overlay analysis and analytical network process to …
An ensemble model for monthly runoff prediction using least squares support vector machine based on variational modal decomposition with dung beetle optimization …
D Xu, Z Li, W Wang - Journal of Hydrology, 2024 - Elsevier
In order to enhance the runoff prediction accuracy, an ensemble prediction model based on
least squares support vector machine (LSSVM) is proposed by including variational mode …
least squares support vector machine (LSSVM) is proposed by including variational mode …
Enhancing environmental sustainability in a critical region: climate change impacts on agriculture and tourism
The Ardabil Plain is pivotal in the national agricultural sector and ranks among the leading
agricultural and horticultural production provinces. The primary objective of this study is to …
agricultural and horticultural production provinces. The primary objective of this study is to …
[HTML][HTML] Determining uncertainties in AI applications in AEC sector and their corresponding mitigation strategies
Y An, H Li, T Su, Y Wang - Automation in Construction, 2021 - Elsevier
Abstract The Artificial Intelligence (AI) methodologies and techniques have been used to
solve a wide spectrum of engineering problems in Architectural, Engineering and …
solve a wide spectrum of engineering problems in Architectural, Engineering and …
Assessing the physical realism of deep learning hydrologic model projections under climate change
S Wi, S Steinschneider - Water Resources Research, 2022 - Wiley Online Library
This study examines whether deep learning models can produce reliable future projections
of streamflow under warming. We train a regional long short‐term memory network (LSTM) …
of streamflow under warming. We train a regional long short‐term memory network (LSTM) …
A research landscape bibliometric analysis on climate change for last decades: Evidence from applications of machine learning
SSM Ajibade, A Zaidi, FV Bekun, AO Adediran… - Heliyon, 2023 - cell.com
Climate change (CC) is one of the greatest threats to human health, safety, and the
environment. Given its current and future impacts, numerous studies have employed …
environment. Given its current and future impacts, numerous studies have employed …
[HTML][HTML] A new methodology for reference evapotranspiration prediction and uncertainty analysis under climate change conditions based on machine learning, multi …
M Kadkhodazadeh, M Valikhan Anaraki… - Sustainability, 2022 - mdpi.com
In the present study, a new methodology for reference evapotranspiration (ETo) prediction
and uncertainty analysis under climate change and COVID-19 post-pandemic recovery …
and uncertainty analysis under climate change and COVID-19 post-pandemic recovery …
[HTML][HTML] Dam system and reservoir operational safety: a meta-research
A Badr, Z Li, W El-Dakhakhni - Water, 2023 - mdpi.com
Dams are critical infrastructure necessary for water security, agriculture, flood risk
management, river navigation, and clean energy generation. However, these multiple, and …
management, river navigation, and clean energy generation. However, these multiple, and …
A novel LSSVM model integrated with GBO algorithm to assessment of water quality parameters
M Kadkhodazadeh, S Farzin - Water Resources Management, 2021 - Springer
In this study, a novel least square support vector machine (LSSVM) model integrated with
gradient-based optimizer (GBO) algorithm is introduced for the assessment of water quality …
gradient-based optimizer (GBO) algorithm is introduced for the assessment of water quality …
[HTML][HTML] Modeling of monthly rainfall–runoff using various machine learning techniques in Wadi Ouahrane Basin, Algeria
MV Anaraki, M Achite, S Farzin, N Elshaboury… - Water, 2023 - mdpi.com
Rainfall–runoff modeling has been the core of hydrological research studies for decades. To
comprehend this phenomenon, many machine learning algorithms have been widely used …
comprehend this phenomenon, many machine learning algorithms have been widely used …