Title : ( Hierarchical hybrid fuzzy-neural networks for modeling of activated carbon preparation for methane storage )
Authors: Hadi Zohreie , Mohammad Ali Fanaei Shykholeslami , Ali Ahmadpour ,
Full TextAbstract
Characterization of porous materials has been an interesting issue for researchers. Conditions and operating parameters of preparing porous materials are very important to reach to required charactristics of porous materials. Some methods have been used for estimation of these parameters for instance neural networks. In this paper hierarchical hybrid-fuzzy neural network (HHFNN) is used for approximation of operating parameters of activated carbon preparation as there are mixed input variables, continuous and discrete. The results show that HHFNN approximate the parameters beter than standard neural network (SNN). Also fewer parameters is needed in HHFNN related to SNN.
Keywords
, HHFNN Modeling activated carbon Adsorption Fuzzy, Neural networks
@inproceedings{paperid:1024997,
author = {Zohreie, Hadi and Fanaei Shykholeslami, Mohammad Ali and Ahmadpour, Ali},
title = {Hierarchical hybrid fuzzy-neural networks for modeling of activated carbon preparation for methane storage},
booktitle = {The 7th International Chemical Engineering Congress& Exhibition},
year = {2011},
location = {جزیره کیش, IRAN},
keywords = {HHFNN
Modeling
activated carbon
Adsorption
Fuzzy- Neural networks},
}
%0 Conference Proceedings
%T Hierarchical hybrid fuzzy-neural networks for modeling of activated carbon preparation for methane storage
%A Zohreie, Hadi
%A Fanaei Shykholeslami, Mohammad Ali
%A Ahmadpour, Ali
%J The 7th International Chemical Engineering Congress& Exhibition
%D 2011
