Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran)

Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran)

The estimation of groundwater levels is crucial and an important step in ensuring sustainable management of water resources. In this paper, selected piezometers of the Hamedan-Bahar plain located in west of Iran. The main objective of this study is to compare effect of various pre-processing methods...

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Bibliographic Details
Main Authors: Mohsen Saroughi, Ehsan Mirzania, Mohammed Achite, Okan Mert Katipoğlu, Nadhir Al-Ansari, Dinesh Kumar Vishwakarma, Il-Moon Chung, Maha Awjan Alreshidi, Krishna Kumar Yadav
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Heliyon
Subjects:
Artificial intelligence
Deep learning
Groundwater level
Hybrid algorithm
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024050370

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