title: Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.
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.
authors.affiliation: Carbolea Research Group, Department of Chemical and Environmental Science, University of Limerick, Ireland.
authors.forename: Daya Shankar
authors.initials: DS
authors.lastname: Pandey
authors.affiliation: Energy, Environment, Modelling and Minerals (E(2)M(2)) Research Section, Department of Earth Science and Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.
authors.forename: Indranil
authors.initials: I
authors.lastname: Pan
authors.affiliation: School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, United Kingdom.
authors.forename: Saptarshi
authors.initials: S
authors.lastname: Das
authors.affiliation: Carbolea Research Group, Department of Chemical and Environmental Science, University of Limerick, Ireland.
authors.forename: James J
authors.initials: JJ
authors.lastname: Leahy
authors.affiliation: Carbolea Research Group, Department of Chemical and Environmental Science, University of Limerick, Ireland. Electronic address: witold.kwapinski@ul.ie.
authors.forename: Witold
authors.initials: W
authors.lastname: Kwapinski
mesh_terms: D000465:Algorithms; D001709:Biotechnology / Q000295:instrumentation* / Q000379:methods*; D005740:Gases / Q000032:analysis*; D008962:Models, Theoretical; D062611:Solid Waste / Q000032:analysis*
chemical_list: D005740:Gases; D062611:Solid Waste
keywords: Fluidized bed gasifier; Gasification; Genetic programming; Municipal solid waste