Table 1 List of related research works.

From: Enhancement of groundwater resources quality prediction by machine learning models on the basis of an improved DRASTIC method

Authors

Methodology

Neshat et al.5,34,26

AHP-AHP, AHP-DRASTIC,DRASTIC-AHP

Neshat et al.36,37

FR-DRASTIC, AHP-DRSTIC, SPSA-DRASTIC

Langerudi et al.38

Fuzzy DRASTIC

Barzegar et al. 1

ANN, SFL, MLF,NF,SCMAI

Baghapour et al.30

ANN for DRASTIC-LU and DRASTIC-N

Barzegar et al.31

ANN-Committee based models (ELM, MARS, SVR, M5 MT)

Nadiri et al.39

SVM-FCF

Hu et al. 40

AHP-DRASTIC

Jesiya and Gopinath33

Fuzzy AHP-DRASTIC

Bordbar et al.32

GWO-GALDIT, GA-GALDIT, Standard-GADIT for Cl/HCO3 pollution evaluation

Torkashvand et al. 41

SWARA and GA-DRASTIC

Bordbar et al.42

GALDIT-FR and GALDIT-GA

Jahromi et al. 43

ABC-SINTACS and GA-SINTACS for nitrate and sulfate pollutions

Norouzi et al.44

RF-DRASTIC is better than GA-DRASTIC

Elzain et al. 45

RBF-NN,RF, and SVM for DRASTIC evaluation

Gharekhani et al. 46

BMA-SVM, BMA-GEP, and BMA-ANN for DRASTIC evaluation

Subbarayan et al. 47

RF, XGB, and CART models for DRASTIC due to nitrate pollution

Karimzadeh-Motlagh et al.48

RF, SVM, GLM

Elzain et al. 46

KNN, ERT, and EBR models for DRASTIC due to land use

  1. SPSA single-parameter sensitivity analysis, AHP analytical hierarchy process,ANN artificial neural network, SFL sugeno fuzzy logic, MFL mamdani fuzzy logic , NF neuro-fuzzy , SCMAI supervised committee machine artificial intelligence method , NVI nitrate vulnerability index, CD composite DRASTIC index, ELM extreme learning machine, MARS multivariate adaptive regression spline, , SVR support vector regression, M5MT M5 model tree , AIMF artificial intelligence multiple framework , FCF fuzzy-catastrophe framework, GWO grey wolf optimizer, GA genetic algorithm, SWARA stepwise weight assessment ratio analysis, ABC artificial bee colony, RF random forest, RBF-NN radial basis function-neural network , ERFR ensemble random forest regression, BMA Bayesian model averaging , GEP gene-expression programming, XGB extreme gradient boosting , CART classification and regression tree, GLM generalized linear model, KNN K-nearest neighborhood, ERT ensemble extremely randomized trees , EBA ensemble bagging regression.
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