Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data

Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data

The accurate assessment of groundwater levels is critical to water resource management. With global warming and climate change, its significance has become increasingly evident, particularly in arid and semi-arid areas. This study compares new extreme learning machines (ELM) methods tuned with metah...

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Bibliographic Details
Main Authors: Rana Muhammad Adnan, Hong-Liang Dai, Reham R. Mostafa, Abu Reza Md. Towfiqul Islam, Ozgur Kisi, Salim Heddam, Mohammad Zounemat-Kermani
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Geocarto International
Subjects:
groundwater prediction
extreme learning machine
particle swarm optimization
grey wolf optimization
whale optimization algorithm
harris hawks optimizer
jellyfish search optimizer
Online Access:http://dx.doi.org/10.1080/10106049.2022.2158951

Internet

http://dx.doi.org/10.1080/10106049.2022.2158951

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