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Genetic algorithm and artificial neural network for engine optimisation of efficiency and NOx emission

dc.contributor.authorKesgin, U
dc.date.accessioned2026-06-27T12:56:31Z
dc.date.issued2004
dc.description.abstractGenetic algorithm (GA) and neural network analysis are used to predict the effects of design and operational parameters on engine efficiency and NOx emissions of a natural gas engine. A computer program to calculate the amount of NOx emissions based on a reaction kinetic model is developed. The validity of this program is verified by measurements from a turbocharged, lean-burn, natural gas engine. Using the results from this program, the effects of operational and design parameters of the engine were investigated. Then a wide range of engine parameters are optimised using a simple GA regarding both efficiency and NOx emissions. Because of the large computation requirements especially for NOx level determination, an artificial neural network model based on results of these investigations is used to predict the engine efficiency and NOx emissions. The results show an increase in efficiency as well as the amount of NOx emissions being kept under the constraint value of 250 mg/Nm3 for stationary engines. (C) 2004 Elsevier Ltd. All rights reserved.en
dc.description.urihttps://doi.org/10.1016/j.fuel.2003.10.025
dc.identifier.doi10.1016/j.fuel.2003.10.025
dc.identifier.eissn1873-7153
dc.identifier.endpage895
dc.identifier.issn0016-2361
dc.identifier.issue7-8
dc.identifier.startpage885
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47941
dc.identifier.volume83
dc.identifier.wos000220387300014
dc.language.isoeng
dc.publisherELSEVIER SCI LTD
dc.relation.ispartofFUEL
dc.subjectengine efficiency
dc.subjectNOx emissions
dc.subjectgenetic algorithm
dc.subjectneural network
dc.subjectEnergy & Fuels
dc.subjectEngineering
dc.titleGenetic algorithm and artificial neural network for engine optimisation of efficiency and NOx emission
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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