A Study of Soft Computing Techniques in Chemical Reactions
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | INFOCOMP: Jornal de Ciência da Computação |
Texto Completo: | https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218 |
Resumo: | This research paper has been described the fuzzy logic and hybrid fuzzy logic-based systems, which is utilize to create knowledge-based frameworks in chemical engineering. In this proposed study, we have proposed fuzzy logic-based methods such as Fuzzy sets, Fuzzy C-Means (FCM), Subtractive Clustering (SC) and integrated approach of SC and Artificial Neural Network Fuzzy Inference System (SC-ANFIS) for calculating the rate of chemical reaction. After comparing the results of these proposed methods with other exiting methods such as classical fuzzy logic, FCM and subtractive clustering (SC) methods, gives get the better result of SC-ANFIS. The root mean square error (both training and testing data) of SC-ANIFIS is less as compared to existing FCM method. |
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INFOCOMP: Jornal de Ciência da Computação |
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A Study of Soft Computing Techniques in Chemical ReactionsThis research paper has been described the fuzzy logic and hybrid fuzzy logic-based systems, which is utilize to create knowledge-based frameworks in chemical engineering. In this proposed study, we have proposed fuzzy logic-based methods such as Fuzzy sets, Fuzzy C-Means (FCM), Subtractive Clustering (SC) and integrated approach of SC and Artificial Neural Network Fuzzy Inference System (SC-ANFIS) for calculating the rate of chemical reaction. After comparing the results of these proposed methods with other exiting methods such as classical fuzzy logic, FCM and subtractive clustering (SC) methods, gives get the better result of SC-ANFIS. The root mean square error (both training and testing data) of SC-ANIFIS is less as compared to existing FCM method. Editora da UFLA2021-06-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218INFOCOMP Journal of Computer Science; Vol. 20 No. 1 (2021): June 20211982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218/566Copyright (c) 2021 Dr. Ramjeet Singh Yadav RSYinfo:eu-repo/semantics/openAccessRSY, Dr. Ramjeet Singh Yadav2021-06-04T11:27:56Zoai:infocomp.dcc.ufla.br:article/1218Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:46.469178INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
A Study of Soft Computing Techniques in Chemical Reactions |
title |
A Study of Soft Computing Techniques in Chemical Reactions |
spellingShingle |
A Study of Soft Computing Techniques in Chemical Reactions RSY, Dr. Ramjeet Singh Yadav |
title_short |
A Study of Soft Computing Techniques in Chemical Reactions |
title_full |
A Study of Soft Computing Techniques in Chemical Reactions |
title_fullStr |
A Study of Soft Computing Techniques in Chemical Reactions |
title_full_unstemmed |
A Study of Soft Computing Techniques in Chemical Reactions |
title_sort |
A Study of Soft Computing Techniques in Chemical Reactions |
author |
RSY, Dr. Ramjeet Singh Yadav |
author_facet |
RSY, Dr. Ramjeet Singh Yadav |
author_role |
author |
dc.contributor.author.fl_str_mv |
RSY, Dr. Ramjeet Singh Yadav |
description |
This research paper has been described the fuzzy logic and hybrid fuzzy logic-based systems, which is utilize to create knowledge-based frameworks in chemical engineering. In this proposed study, we have proposed fuzzy logic-based methods such as Fuzzy sets, Fuzzy C-Means (FCM), Subtractive Clustering (SC) and integrated approach of SC and Artificial Neural Network Fuzzy Inference System (SC-ANFIS) for calculating the rate of chemical reaction. After comparing the results of these proposed methods with other exiting methods such as classical fuzzy logic, FCM and subtractive clustering (SC) methods, gives get the better result of SC-ANFIS. The root mean square error (both training and testing data) of SC-ANIFIS is less as compared to existing FCM method. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-13 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218 |
url |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1218/566 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Dr. Ramjeet Singh Yadav RSY info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Dr. Ramjeet Singh Yadav RSY |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora da UFLA |
publisher.none.fl_str_mv |
Editora da UFLA |
dc.source.none.fl_str_mv |
INFOCOMP Journal of Computer Science; Vol. 20 No. 1 (2021): June 2021 1982-3363 1807-4545 reponame:INFOCOMP: Jornal de Ciência da Computação instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
INFOCOMP: Jornal de Ciência da Computação |
collection |
INFOCOMP: Jornal de Ciência da Computação |
repository.name.fl_str_mv |
INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
infocomp@dcc.ufla.br||apfreire@dcc.ufla.br |
_version_ |
1799874742653550592 |