The evaluation of potentially toxic elements using artificial neural networks and fuzzy linear regression analysis methods in cappadocian volcanic ash soils of Turkey

Fuzzy Machine Learning Applications in Environmental Engineering: Does the Ability to Deal with Uncertainty Really Matter?

“…Goyal et al [21] Daily Evaporation ANN, LS-SVR, FIS, ANFIS Ay and Kisi [22] COD Concentration MLR, MLP, RBF, GRNN, ANFIS, k-MLP He et al [23] River Flow ANN, ANFIS, SVM Asadi et al [24] NOx Concentration ANN, NF Tayfur et al [25] Hydraulic Conductivity SFL, MFL, LM-ANN, NF Piotrowski et al [26] Water Temperature MLP, ANFIS, WNN, KNN Olyaie et al [27] Suspended Sediment Load ANNs, ANFIS, WNN, SRC Estalaki et al [28] Water Quality ER, FSC, SWMM, MUSIC Aghbashlo et al [29] Photo-Biohydrogen Production RBF, FCR Nadiri et al [30] Strength of Geopolymers SFL, MFL, LFL Bagheri et al [31] Landfill Leachate Penetration FIS, ANN Bressane et al [32] Arboreal Recognition FIS, C5, CCNN, KNN, PNN, MLP, RF, DT, SGB, SVM Nabavi-Pelesaraei et al [33] Energy Output ANN, ANFIS Dou and Yang [34] Daily Evapotranspiration ELM, ANFIS, ANN, SVM Choubin et al [35] Suspended Sediment Load CART, ANFIS, MLP, SVM Nadiri et al [36] Effluent Water Parameters FIS, SCFL Raei et al [37] Urban Stormwater MLP, NSGA-II, Fuzzy α-cut, DSS Adnan et al [38] Daily Streamflow ANFIS-PSO, MARS, M5, OP-ELM Kaab et al [39] Environmental Impacts ANN, ANFIS Roy et al [40] Reference Evapotranspiration FA-ANFIS, Ensembles Ly et al [41] Water Quality Modeling LR, DL-ANN, ANFIS Manzar et al [42] Water Quality Index GRNN, Elm-NN, FFNN, SVM, LR, NF Kılıç and Topuz [43] PTE in Volcanic Ash Soils ANN, FLRA Recognizing the inherent uncertainties in climatic conditions, Goyal et al [21] aimed to address the challenges associated with the accurate modeling of daily evaporation predictions in subtropical climates. The methods under comparison included ANN, least squares support vector regression (LS-SVR), FIS, and adaptive neuro-fuzzy inference systems (ANFISs).…”

“…Kılıç and Topuz [43] aimed to estimate the concentration of potentially toxic elements (PTEs) in Cappadocian volcanic ash soils, employing ANN and fuzzy linear regression analysis (FLRA). The study revealed that the FLRA method exhibited the lowest error and high R 2 values in comparison to the ANN method.…”