Groundwater level prediction using machine learning models: A comprehensive review

Hai, Tao; Majeed Hameed, Mohammed; Abdulameer Marhoon, Haydar; Zounemat‐Kermani, Mohammad; Heddam, Salim; Kim, Sungwon; Oleiwi Sulaiman, Sadeq; Leong Tan, Mou; Sa’adi, Zulfaqar; Danandeh Mehr, Ali; Falah Allawi, Mohammed; I. Abba, Sani; Mohamad Zain, Jasni; W. Falah, Mayadah; Jamei, Mehdi; Dhanraj Bokde, Neeraj; Bayatvarkeshi, Maryam; Al-Mukhtar, Mustafa; Kumar Bhagat, Suraj; Tiyasha, Tiyasha; Mohamed Khedher, Khaled; Al‐Ansari, Nadhir; Shahid, Shamsuddin; Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Zaher

doi:10.1016/j.neucom.2022.03.014

Public

Groundwater level prediction using machine learning models: A comprehensive review

Published in Neurocomputing • Mar 14, 2022

Authors:

Tao Hai

Mohammed Majeed Hameed

Haydar Abdulameer Marhoon

Abstract

Developing accurate soft computing methods for groundwater level (GWL) forecasting is essential for enhancing the planning and management of water resources. Over the past two decades, significant progress has been made in GWL prediction using machine learning (ML) models. Several review articles ha...

Subject

Computer science

Field (mathematics)

Machine learning

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