Application of machine learning in water resources management: A systematic literature review

F Ghobadi, D Kang - Water, 2023 - mdpi.com
In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …

The role of artificial intelligence and digital technologies in dam engineering: Narrative review and outlook

MA Hariri-Ardebili, G Mahdavi, LK Nuss… - Engineering Applications of …, 2023 - Elsevier
This narrative review paper explores the diverse applications of artificial intelligence (AI) in
the field of dam engineering. Authored by research engineers specializing in civil …

Advanced machine learning techniques to improve hydrological prediction: A comparative analysis of streamflow prediction models

V Kumar, N Kedam, KV Sharma, DJ Mehta, T Caloiero - Water, 2023 - mdpi.com
The management of water resources depends heavily on hydrological prediction, and
advances in machine learning (ML) present prospects for improving predictive modelling …

Develo** bearing capacity model for geogrid-reinforced stone columns improved soft clay utilizing MARS-EBS hybrid method

AR Ghanizadeh, A Ghanizadeh, PG Asteris… - Transportation …, 2023 - Elsevier
Because of the complicated geometry and a lack of knowledge about the parameters that
impact it, estimating the ultimate bearing capacity (q rs) of a geogrid-reinforced sandy bed …

An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical …

W Wang, Q Cheng, K Chau, H Hu, H Zang, D Xu - Journal of Hydrology, 2023 - Elsevier
Reliable runoff prediction plays a significant role in reservoir scheduling, water resources
management, and efficient utilization of water resources. To effectively enhance the …

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 …

An inclusive survey on marine predators algorithm: Variants and applications

R Rai, KG Dhal, A Das, S Ray - Archives of Computational Methods in …, 2023 - Springer
Abstract Marine Predators Algorithm (MPA) is the existing population-based meta-heuristic
algorithms that falls under the category of Nature-Inspired Optimization Algorithm (NIOA) …

Metaheuristic approaches for prediction of water quality indices with relief algorithm-based feature selection

NL Kushwaha, J Rajput, T Suna, DR Sena… - Ecological …, 2023 - Elsevier
Monitoring and assessing groundwater quality are important for sustainable water resource
management. Therefore, the present study aimed to analyze and predict the water quality …

Several tree-based solutions for predicting flyrock distance due to mine blasting

M Yari, DJ Armaghani, C Maraveas, AN Ejlali… - Applied Sciences, 2023 - mdpi.com
Blasting operations involve some undesirable environmental issues that may cause damage
to equipment and surrounding areas. One of them, and probably the most important one, is …

Data-driven optimized artificial neural network technique for prediction of flyrock induced by boulder blasting

X Wang, S Hosseini, D Jahed Armaghani… - Mathematics, 2023 - mdpi.com
One of the most undesirable consequences induced by blasting in open-pit mines and civil
activities is flyrock. Furthermore, the production of oversize boulders creates many problems …