Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine

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dc.contributor.authorTasdemir, Sakir
dc.contributor.authorSaritas, Ismail
dc.contributor.authorCiniviz, Murat
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2020-03-26T18:13:48Z
dc.date.available2020-03-26T18:13:48Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis study is deals with artificial neural network (ANN) and fuzzy expert system (FES) modelling of a gasoline engine to predict engine power, torque, specific fuel consumption and hydrocarbon emission. In this study, experimental data, which were obtained from experimental studies in a laboratory environment, have been used. Using some of the experimental data for training and testing an ANN for the engine was developed. Also the FES has been developed and realized. In this systems output parameters power, torque, specific fuel consumption and hydrocarbon emission have been determined using input parameters intake valve opening advance and engine speed. When experimental data and results obtained from ANN and FES were compared by t-test in SPSS and regression analysis in Matlab, it was determined that both groups of data are consistent with each other for p > 0.05 confidence interval and differences were statistically not significant. As a result, it has been shown that developed ANN and FES can be used reliably in automotive industry and engineering instead of experimental work. (C) 2011 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipSelcuk University's Scientific Research UnitSelcuk Universityen_US
dc.description.sponsorshipThis study has been supported by Selcuk University's Scientific Research Unit.en_US
dc.identifier.doi10.1016/j.eswa.2011.04.198en_US
dc.identifier.endpage13923en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue11en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage13912en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2011.04.198
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26163
dc.identifier.volume38en_US
dc.identifier.wosWOS:000294084700046en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectFuzzy expert systemen_US
dc.subjectArtificial neural networken_US
dc.subjectEngine performanceen_US
dc.subjectEngine emissionen_US
dc.titleArtificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engineen_US
dc.typeArticleen_US

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