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Mathematical and ANN Models of the Effect of Dosage on Cu 2+ Sorption Capacity of Luffa Cylindrica

Mathematical and ANN Models of the Effect of Dosage on Cu 2+ Sorption Capacity of Luffa Cylindrica The biosorption of copper (II) ions onto Luffa cylindrica was investigated. Luffa cylindrica, a biomaterial with wide distribution particularly in the tropical world, is characterized with the surface area, chemical bonds, bulk density, pore size distribution, microstructures, composition, morphology and elemental composition which are determined. Biosorption studies were carried out with varying dosage and the experimental data obtained were fitted to Pseudo-Second order kinetic model. The regression value obtained from the various doses studies ranged from 0.991 to 0.999. A kinectic model was developed mathematically and as well Artificial Neural Network (ANN) was applied to develop a Multiple Input Single Output (MISO) back propagation neural network model which was validated. The RMSE value was found to be 1.2754. Artificial neural network has the capability to predict the sorption capacity quite reasonably for the model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Solids and Structures Science and Engineering Publishing Company

Mathematical and ANN Models of the Effect of Dosage on Cu 2+ Sorption Capacity of Luffa Cylindrica

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Publisher
Science and Engineering Publishing Company
Copyright
Science and Engineering Publishing Company
ISSN
2327-1728
eISSN
2327-1736

Abstract

The biosorption of copper (II) ions onto Luffa cylindrica was investigated. Luffa cylindrica, a biomaterial with wide distribution particularly in the tropical world, is characterized with the surface area, chemical bonds, bulk density, pore size distribution, microstructures, composition, morphology and elemental composition which are determined. Biosorption studies were carried out with varying dosage and the experimental data obtained were fitted to Pseudo-Second order kinetic model. The regression value obtained from the various doses studies ranged from 0.991 to 0.999. A kinectic model was developed mathematically and as well Artificial Neural Network (ANN) was applied to develop a Multiple Input Single Output (MISO) back propagation neural network model which was validated. The RMSE value was found to be 1.2754. Artificial neural network has the capability to predict the sorption capacity quite reasonably for the model.

Journal

Solids and StructuresScience and Engineering Publishing Company

Published: Jun 1, 2013

Keywords: Sorption Capacity; Luffa Cylindrica; Biosorption; Mathematical Modelling; Artificial Neural Network

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