Prediction of adsorption efficiencies of Ni (II) in aqueous solutions with perlite via artificial neural networks

• Autorzy: Turp S. M.

Identyfikatory

DOI

10.1515/aep-2017-0034

• Języki publikacji: EN

Abstrakty

EN

This study investigates the estimated adsorption efficiency of artificial Nickel (II) ions with perlite in an aqueous solution using artificial neural networks, based on 140 experimental data sets. Prediction using artificial neural networks is performed by enhancing the adsorption efficiency with the use of Nickel (II) ions, with the initial concentrations ranging from 0.1 mg/L to 10 mg/L, the adsorbent dosage ranging from 0.1 mg to 2 mg, and the varying time of effect ranging from 5 to 30 mins. This study presents an artificial neural network that predicts the adsorption efficiency of Nickel (II) ions with perlite. The best algorithm is determined as a quasi-Newton back-propagation algorithm. The performance of the artificial neural network is determined by coefficient determination (R²), and its architecture is 3-12-1. The prediction shows that there is an outstanding relationship between the experimental data and the predicted values.

Słowa kluczowe

EN

wastewater; treatment efficiency; adsorption; perlite; artificial neural network

• Wydawca: Institute of Environmental Engineering, Polish Academy of Sciences
• Czasopismo: Archives of Environmental Protection
• Rocznik: 2017
• Tom: Vol. 43, no. 4
• Strony: 26--32
• Opis fizyczny: Bibliogr. 17 poz., rys., tab., wykr.

Twórcy

autor

Turp S. M.

• Bitlis Eren University, Turkey Faculty of Architecture and Engineering, Department of Environmental Engineering

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).