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Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier

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Show simple item record Pandey, Daya Shankar Pan, Indranil Das, Saptarshi Leahy, James J. Kwapinski, Witold 2018-08-30T15:16:48Z 2018-08-30T15:16:48Z 2015
dc.description peer-reviewed en_US
dc.description This article corresponds to chapter 6 of Ph.D: Experimental and mathematical modelling of biowaste gasification in a bubbling fluidised bed reactor Pandey, Daya Shankar URI:
dc.description.abstract A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. en_US
dc.language.iso eng en_US
dc.publisher Elsevier en_US
dc.relation info:eu-repo/grantAgreement/EC/FP7/289887 en_US
dc.relation.ispartofseries Bioresource Technology;179, pp. 524-533
dc.rights This is the author’s version of a work that was accepted for publication in Bioresource Technology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Bioresource Technology, 2015, 179, pp. 524-533, en_US
dc.subject municipal solid waste en_US
dc.subject genetic programming en_US
dc.subject gasification en_US
dc.subject fluidized bed gasifier en_US
dc.title Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1016/j.biortech.2014.12.048
dc.contributor.sponsor ERC en_US
dc.relation.projectid 289887 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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