Global Perspectives on Artificial Intelligence, Volume (1), No (2), Year (2013-7) , Pages (40-48)

Title : ( Simulation of an Improved Cyclone System by Artificial Neural Network, Adaptive-network-based Fuzzy Inference System and Hybrid ANN-genetic Algorithm Approach )

Authors: Javad Sargolzaei , Amin Hedayati Moghaddam , mohsen alizadeh ,
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Simulation of an improved cyclone was carried out by means of Artificial Neural Networks (ANNs), adaptive-network-based fuzzy inference system (ANFIS), and hybrid ANN-Genetic Algorithm (GA). The apparatus consists of two cyclones coupled with a specially designed cylindrical chamber, which includes a rotating tube inside with air-impinging nuzzles drilled on the peripheral surface of the tube. The chamber includes a tube with nozzles on its peripheral surface from which jet-impingement flow throws the particles nearer to wall of the chamber. Efficiency of the jet-impingement chamber, as a function of flow rate on the feed, recycle, jet-impingement along with jet-impingement tube rotational speed, has been tested. ANN, ANFIS, and hybrid ANN-GA are capable to accurately capture the non-linear characteristics of the chamber performance.

Keywords

, Dust Removal, Jet-Impingement, Genetic Algorithm, Neural Network,
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@article{paperid:1036887,
author = {Sargolzaei, Javad and Hedayati Moghaddam, Amin and Alizadeh, Mohsen},
title = {Simulation of an Improved Cyclone System by Artificial Neural Network, Adaptive-network-based Fuzzy Inference System and Hybrid ANN-genetic Algorithm Approach},
journal = {Global Perspectives on Artificial Intelligence},
year = {2013},
volume = {1},
number = {2},
month = {July},
issn = {2327-7289},
pages = {40--48},
numpages = {8},
keywords = {Dust Removal; Jet-Impingement; Genetic Algorithm; Neural Network; ANFIS},
}

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%0 Journal Article
%T Simulation of an Improved Cyclone System by Artificial Neural Network, Adaptive-network-based Fuzzy Inference System and Hybrid ANN-genetic Algorithm Approach
%A Sargolzaei, Javad
%A Hedayati Moghaddam, Amin
%A Alizadeh, Mohsen
%J Global Perspectives on Artificial Intelligence
%@ 2327-7289
%D 2013

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