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Journal Abstract Search

689 related items for PubMed ID: 32556670

  • 1. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel.
    Wong YJ, Arumugasamy SK, Chung CH, Selvarajoo A, Sethu V.
    Environ Monit Assess; 2020 Jun 17; 192(7):439. PubMed ID: 32556670
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  • 2. Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.
    Claude BJ, Onyango MS.
    J Environ Sci Health A Tox Hazard Subst Environ Eng; 2024 Jun 17; 59(4):172-179. PubMed ID: 38613163
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  • 5. Improving one-dimensional pollution dispersion modeling in rivers using ANFIS and ANN-based GA optimized models.
    Seifi A, Riahi-Madvar H.
    Environ Sci Pollut Res Int; 2019 Jan 17; 26(1):867-885. PubMed ID: 30415370
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  • 7. A novel artificial intelligent model for predicting water treatment efficiency of various biochar systems based on artificial neural network and queuing search algorithm.
    Zheng X, Nguyen H.
    Chemosphere; 2022 Jan 17; 287(Pt 3):132251. PubMed ID: 34826934
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  • 8. Adaptive neuro-fuzzy inference system (ANFIS): a new approach to predictive modeling in QSAR applications: a study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists.
    Buyukbingol E, Sisman A, Akyildiz M, Alparslan FN, Adejare A.
    Bioorg Med Chem; 2007 Jun 15; 15(12):4265-82. PubMed ID: 17434739
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  • 11. Evaluation of multilayer perceptron neural networks and adaptive neuro-fuzzy inference systems for the mass transfer modeling of Echium amoenum Fisch. & C. A. Mey.
    Chasiotis V, Nadi F, Filios A.
    J Sci Food Agric; 2021 Dec 15; 101(15):6514-6524. PubMed ID: 34000064
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  • 12. Application of artificial neural networks to predict the heavy metal contamination in the Bartin River.
    Ucun Ozel H, Gemici BT, Gemici E, Ozel HB, Cetin M, Sevik H.
    Environ Sci Pollut Res Int; 2020 Dec 15; 27(34):42495-42512. PubMed ID: 32705560
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  • 16. Comparison of different heuristic and decomposition techniques for river stage modeling.
    Seo Y, Kim S, Singh VP.
    Environ Monit Assess; 2018 Jun 12; 190(7):392. PubMed ID: 29892912
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  • 18. Predicting coagulation-flocculation process for turbidity removal from water using graphene oxide: a comparative study on ANN, SVR, ANFIS, and RSM models.
    Ghasemi M, Hasani Zonoozi M, Rezania N, Saadatpour M.
    Environ Sci Pollut Res Int; 2022 Oct 12; 29(48):72839-72852. PubMed ID: 35616836
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