Groundwater level prediction using machine learning models: A comprehensive review
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...
الحاوية / القاعدة: | Neurocomputing |
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المؤلف الرئيسي: | Tao H.; Hameed M.M.; Marhoon H.A.; Zounemat-Kermani M.; Heddam S.; Sungwon K.; Sulaiman S.O.; Tan M.L.; Sa'adi Z.; Mehr A.D.; Allawi M.F.; Abba S.I.; Zain J.M.; Falah M.W.; Jamei M.; Bokde N.D.; Bayatvarkeshi M.; Al-Mukhtar M.; Bhagat S.K.; Tiyasha T.; Khedher K.M.; Al-Ansari N.; Shahid S.; Yaseen Z.M. |
التنسيق: | Short survey |
اللغة: | English |
منشور في: |
Elsevier B.V.
2022
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الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126854743&doi=10.1016%2fj.neucom.2022.03.014&partnerID=40&md5=5e95b9575d5950f1af161383a5fd77ee |
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Groundwater level prediction using machine learning models: A comprehensive review
بواسطة: 2-s2.0-85126854743
منشور في: (2022)