Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process

In this paper, an application of a neuro-fuzzy modeling approach is presented in order to characterize the essential behavior of enzymatic esterification processes. The accuracy of the developed model was validated by comparing the response of the model and actual experimental data. The simulation r...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of chemical engineering and applications (IJCEA) 2011-12, Vol.2 (6), p.408-408
Hauptverfasser: Chaibakhsh, A, Chaibakhsh, N, Rahman, M B Abdul
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 408
container_issue 6
container_start_page 408
container_title International journal of chemical engineering and applications (IJCEA)
container_volume 2
creator Chaibakhsh, A
Chaibakhsh, N
Rahman, M B Abdul
description In this paper, an application of a neuro-fuzzy modeling approach is presented in order to characterize the essential behavior of enzymatic esterification processes. The accuracy of the developed model was validated by comparing the response of the model and actual experimental data. The simulation results showed good generalization of the proposed model and its ability to predict the reaction yield, where the error of prediction for training data was less than 3%, and for validating and testing data less than 3 and 1.5%, respectively. A model-based optimization was performed to obtain the best operating conditions by using genetic algorithm. A fair comparison between the optimization results obtained from simulation experiments and laboratory data indicated the accuracy and feasibility of the proposed approach for estimating the optimal profiles in biotechnological processes. This can further facilitate up-scaling of the process by selecting the appropriate combinations of potential manufacturing parameters.
doi_str_mv 10.7763/IJCEA.2011.V2.143
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1701045458</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1701045458</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1993-2defd3affdb605c4cd078314cd16ea60b355c19365716e338afb51930fdca25d3</originalsourceid><addsrcrecordid>eNqFkLtOwzAUhj2ARFX6AGweWRJ8iXMZqyqFVkVFCLpari_IKImDnQ7N0-MSmJl-_UffOdL5ALjDKC2KnD5stqt6mRKEcXogKc7oFZjFhhJECL4BixA-EYqd0gpXM_C67PvGSjFY10Fn4Po0jmf47JRubPcBRafgvh9sa8cJsR2su_HcxiZhHQbtrflbf_FO6hBuwbURTdCL35yD93X9tnpKdvvHzWq5SySuKpoQpY2iwhh1zBGTmVSoKCmOiXMtcnSkjEWS5qyIA0pLYY4sdmSUFIQpOgf3093eu6-TDgNvbZC6aUSn3SlwXMQ3M5ax8n-UEVRlVZGziOIJld6F4LXhvbet8GeOEb8Y5j-G-cUwPxAeDdNvM41xAA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1520949765</pqid></control><display><type>article</type><title>Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Chaibakhsh, A ; Chaibakhsh, N ; Rahman, M B Abdul</creator><creatorcontrib>Chaibakhsh, A ; Chaibakhsh, N ; Rahman, M B Abdul</creatorcontrib><description>In this paper, an application of a neuro-fuzzy modeling approach is presented in order to characterize the essential behavior of enzymatic esterification processes. The accuracy of the developed model was validated by comparing the response of the model and actual experimental data. The simulation results showed good generalization of the proposed model and its ability to predict the reaction yield, where the error of prediction for training data was less than 3%, and for validating and testing data less than 3 and 1.5%, respectively. A model-based optimization was performed to obtain the best operating conditions by using genetic algorithm. A fair comparison between the optimization results obtained from simulation experiments and laboratory data indicated the accuracy and feasibility of the proposed approach for estimating the optimal profiles in biotechnological processes. This can further facilitate up-scaling of the process by selecting the appropriate combinations of potential manufacturing parameters.</description><identifier>ISSN: 2010-0221</identifier><identifier>DOI: 10.7763/IJCEA.2011.V2.143</identifier><language>eng</language><subject>Accuracy ; Chemical engineering ; Computer simulation ; Esterification ; Fuzzy ; Fuzzy logic ; Mathematical models ; Optimization</subject><ispartof>International journal of chemical engineering and applications (IJCEA), 2011-12, Vol.2 (6), p.408-408</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1993-2defd3affdb605c4cd078314cd16ea60b355c19365716e338afb51930fdca25d3</citedby><cites>FETCH-LOGICAL-c1993-2defd3affdb605c4cd078314cd16ea60b355c19365716e338afb51930fdca25d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Chaibakhsh, A</creatorcontrib><creatorcontrib>Chaibakhsh, N</creatorcontrib><creatorcontrib>Rahman, M B Abdul</creatorcontrib><title>Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process</title><title>International journal of chemical engineering and applications (IJCEA)</title><description>In this paper, an application of a neuro-fuzzy modeling approach is presented in order to characterize the essential behavior of enzymatic esterification processes. The accuracy of the developed model was validated by comparing the response of the model and actual experimental data. The simulation results showed good generalization of the proposed model and its ability to predict the reaction yield, where the error of prediction for training data was less than 3%, and for validating and testing data less than 3 and 1.5%, respectively. A model-based optimization was performed to obtain the best operating conditions by using genetic algorithm. A fair comparison between the optimization results obtained from simulation experiments and laboratory data indicated the accuracy and feasibility of the proposed approach for estimating the optimal profiles in biotechnological processes. This can further facilitate up-scaling of the process by selecting the appropriate combinations of potential manufacturing parameters.</description><subject>Accuracy</subject><subject>Chemical engineering</subject><subject>Computer simulation</subject><subject>Esterification</subject><subject>Fuzzy</subject><subject>Fuzzy logic</subject><subject>Mathematical models</subject><subject>Optimization</subject><issn>2010-0221</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkLtOwzAUhj2ARFX6AGweWRJ8iXMZqyqFVkVFCLpari_IKImDnQ7N0-MSmJl-_UffOdL5ALjDKC2KnD5stqt6mRKEcXogKc7oFZjFhhJECL4BixA-EYqd0gpXM_C67PvGSjFY10Fn4Po0jmf47JRubPcBRafgvh9sa8cJsR2su_HcxiZhHQbtrflbf_FO6hBuwbURTdCL35yD93X9tnpKdvvHzWq5SySuKpoQpY2iwhh1zBGTmVSoKCmOiXMtcnSkjEWS5qyIA0pLYY4sdmSUFIQpOgf3093eu6-TDgNvbZC6aUSn3SlwXMQ3M5ax8n-UEVRlVZGziOIJld6F4LXhvbet8GeOEb8Y5j-G-cUwPxAeDdNvM41xAA</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Chaibakhsh, A</creator><creator>Chaibakhsh, N</creator><creator>Rahman, M B Abdul</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20111201</creationdate><title>Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process</title><author>Chaibakhsh, A ; Chaibakhsh, N ; Rahman, M B Abdul</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1993-2defd3affdb605c4cd078314cd16ea60b355c19365716e338afb51930fdca25d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Accuracy</topic><topic>Chemical engineering</topic><topic>Computer simulation</topic><topic>Esterification</topic><topic>Fuzzy</topic><topic>Fuzzy logic</topic><topic>Mathematical models</topic><topic>Optimization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chaibakhsh, A</creatorcontrib><creatorcontrib>Chaibakhsh, N</creatorcontrib><creatorcontrib>Rahman, M B Abdul</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of chemical engineering and applications (IJCEA)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chaibakhsh, A</au><au>Chaibakhsh, N</au><au>Rahman, M B Abdul</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process</atitle><jtitle>International journal of chemical engineering and applications (IJCEA)</jtitle><date>2011-12-01</date><risdate>2011</risdate><volume>2</volume><issue>6</issue><spage>408</spage><epage>408</epage><pages>408-408</pages><issn>2010-0221</issn><abstract>In this paper, an application of a neuro-fuzzy modeling approach is presented in order to characterize the essential behavior of enzymatic esterification processes. The accuracy of the developed model was validated by comparing the response of the model and actual experimental data. The simulation results showed good generalization of the proposed model and its ability to predict the reaction yield, where the error of prediction for training data was less than 3%, and for validating and testing data less than 3 and 1.5%, respectively. A model-based optimization was performed to obtain the best operating conditions by using genetic algorithm. A fair comparison between the optimization results obtained from simulation experiments and laboratory data indicated the accuracy and feasibility of the proposed approach for estimating the optimal profiles in biotechnological processes. This can further facilitate up-scaling of the process by selecting the appropriate combinations of potential manufacturing parameters.</abstract><doi>10.7763/IJCEA.2011.V2.143</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2010-0221
ispartof International journal of chemical engineering and applications (IJCEA), 2011-12, Vol.2 (6), p.408-408
issn 2010-0221
language eng
recordid cdi_proquest_miscellaneous_1701045458
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Accuracy
Chemical engineering
Computer simulation
Esterification
Fuzzy
Fuzzy logic
Mathematical models
Optimization
title Application of Fuzzy Modeling and Optimization in Enzymatic Esterification Process
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T17%3A09%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Application%20of%20Fuzzy%20Modeling%20and%20Optimization%20in%20Enzymatic%20Esterification%20Process&rft.jtitle=International%20journal%20of%20chemical%20engineering%20and%20applications%20(IJCEA)&rft.au=Chaibakhsh,%20A&rft.date=2011-12-01&rft.volume=2&rft.issue=6&rft.spage=408&rft.epage=408&rft.pages=408-408&rft.issn=2010-0221&rft_id=info:doi/10.7763/IJCEA.2011.V2.143&rft_dat=%3Cproquest_cross%3E1701045458%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1520949765&rft_id=info:pmid/&rfr_iscdi=true