Particle swarm and grey wolf optimization: enhancing groundwater quality models through artificial neural networks-Reference-Cited by-同舟云学术

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Particle swarm and grey wolf optimization: enhancing groundwater quality models through artificial neural networks

Published:2023-11-18 Issue: Volume: Page:
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Sahour Soheil,Khanbeyki Matin,Gholami Vahid,Sahour Hossein,Karimi Hadi,Mohammadi Mohsen

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-023-02610-1.pdf

Reference63 articles.

1. Alshehri F, Sultan M, Karki S, Alwagdani E, Alsefry S, Alharbi H, Sahour H, Sturchio N (2020) Mapping the distribution of shallow groundwater occurrences using Remote sensing-based statistical modeling over southwest Saudi Arabia. Remote Sens 12(9):1361. https://doi.org/10.3390/rs12091361

2. Bahrami S, Doulati Ardejani F, Baafi E (2016) Application of artificial neural network coupled with genetic algorithm and simulated annealing to solve groundwater inflow problem to an advancing open pit mine. J Hydrol 36:471–484. https://doi.org/10.1016/j.jhydrol.2016.03.002

3. Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge, UK

4. Carroll RW, Deems JS, Niswonger R, Schumer R, Williams KH (2019) The importance of interflow to groundwater recharge in a snowmelt-dominated headwater basin. Geophys Res Lett 46(11):5899–5908

5. Ch S, Mathur S (2012) Particle swarm optimization trained neural network for aquifer parameter estimation. KSCE J Civ Eng 16:298–307

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