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

Pandey, Daya S. and Pan, Indranil and Das, Saptarshi and Leahy, James J. and Kwapinski, Witold (2015) Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier. Bioresource Technology, 179. pp. 524-533. ISSN 1873-2976

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Official URL: http://dx.doi.org/10.1016/j.biortech.2014.12.048

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.

Item Type: Journal Article
Keywords: Municipal solid waste, Genetic programming, Gasification, Fluidized bed gasifier
Faculty: Faculty of Science & Technology
SWORD Depositor: Symplectic User
Depositing User: Symplectic User
Date Deposited: 02 Apr 2019 09:04
Last Modified: 02 Apr 2019 10:10
URI: http://arro.anglia.ac.uk/id/eprint/704225

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