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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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dc.contributor.author Pandey, Daya Shankar
dc.contributor.author Pan, Indranil
dc.contributor.author Das, Saptarshi
dc.contributor.author Leahy, James J.
dc.contributor.author Kwapinski, Witold
dc.date.accessioned 2018-08-30T15:16:48Z
dc.date.available 2018-08-30T15:16:48Z
dc.date.issued 2015
dc.identifier.uri http://hdl.handle.net/10344/7122
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: http://hdl.handle.net/10344/7116
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.relation.uri http://dx.doi.org/10.1016/j.biortech.2014.12.048
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, http://dx.doi.org/10.1016/j.biortech.2014.12.048 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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