Estimation of Unconfined Aquifer Transmissivity Using a Comparative Study of Machine Learning Models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03588-9.pdf
Reference72 articles.
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2. Ayvaz MT (2007) Simultaneous determination of aquifer parameters and zone structures with fuzzy c-means clustering and meta-heuristic harmony search algorithm. Adv Water Resour 30(11):2326–2338. https://doi.org/10.1016/j.advwatres.2007.05.009
3. Azari T, Samani N (2018) Modeling the Neuman’s well function by an artificial neural network for the determination of unconfined aquifer parameters. Comput Geosci 22(4):1135–1148. https://doi.org/10.1007/s10596-018-9742-8
4. Azari T, Samani N, Mansoori E (2015) An artificial neural network model for the determination of leaky confined aquifer parameters: an accurate alternative to type curve matching methods. Iran J Sci Technol (Sci) 39(4):463–472. https://doi.org/10.22099/IJSTS.2015.3389
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