Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN

Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN

In the present study, six meta-heuristic schemes are hybridized with artificial neural network (ANN), adaptive neuro-fuzzy interface system (ANFIS), and support vector machine (SVM), to predict monthly groundwater level (GWL), evaluate uncertainty analysis of predictions and spatial variation analys...

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Bibliographic Details
Main Authors: Akram Seifi, Mohammad Ehteram, Vijay P. Singh, Amir Mosavi
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sustainability
Subjects:
groundwater
artificial intelligence
hydrologic model
groundwater level prediction
machine learning
principal component analysis
Online Access:https://www.mdpi.com/2071-1050/12/10/4023

Internet

https://www.mdpi.com/2071-1050/12/10/4023

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