13th Iranian National Chemical Engineering Congress & 1st International Regional Chemical and Petroleum Engineering , 2010-10-25

Title : ( A novel Approach in Predicting the Adsorption Behavior of Activated and Molecular Sieve Carbons )

Authors: Nasser Saghatoleslami , Gholamhossein Vatan khah , mosayeb amiri ,

Citation: BibTeX | EndNote

Artificial neural network (i.e., ANN) method has been adopted in this work to predict the equilibrium adsorption behavior of methane and ethylene for four different carbon adsorbent types. The result has been compared with both empirical models such as Langmuir, Freundlich, UNILAN, Sips and Toth and experimental data. The results revealed that artificial neural network is a powerful and accurate method in predicting the adsorption behaviors of various types of activated and molecular sieve carbons, in contrast with other empirical models and with mean absolute errors of training and testing nets of 0.00000546 and 0.000378.

Keywords

, Ethylene, Methane, ANN, Adsorption Isotherm, Molecular Sieve, Activated
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@inproceedings{paperid:1018127,
author = {Saghatoleslami, Nasser and Vatan Khah, Gholamhossein and Amiri, Mosayeb},
title = {A novel Approach in Predicting the Adsorption Behavior of Activated and Molecular Sieve Carbons},
booktitle = {13th Iranian National Chemical Engineering Congress & 1st International Regional Chemical and Petroleum Engineering},
year = {2010},
location = {کرمانشاه, IRAN},
keywords = {Ethylene; Methane; ANN; Adsorption Isotherm; Molecular Sieve; Activated Carbon.},
}

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%0 Conference Proceedings
%T A novel Approach in Predicting the Adsorption Behavior of Activated and Molecular Sieve Carbons
%A Saghatoleslami, Nasser
%A Vatan Khah, Gholamhossein
%A Amiri, Mosayeb
%J 13th Iranian National Chemical Engineering Congress & 1st International Regional Chemical and Petroleum Engineering
%D 2010

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