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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Bibliografiske detaljer

Principais autores:	Rana Muhammad Adnan, Hong-Liang Dai, Reham R. Mostafa, Abu Reza Md. Towfiqul Islam, Ozgur Kisi, Salim Heddam, Mohammad Zounemat-Kermani
Format:	Artigo
Sprog:	Inglês
Udgivet:	Taylor & Francis Group 2023-12-01
Serier:	Geocarto International
Fag:	groundwater prediction extreme learning machine particle swarm optimization grey wolf optimization whale optimization algorithm harris hawks optimizer jellyfish search optimizer
Online adgang:	http://dx.doi.org/10.1080/10106049.2022.2158951
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