title: Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor.
abstract: In this paper, multi-layer feed forward neural networks are used to predict the lower heating value of gas (LHV), lower heating value of gasification products including tars and entrained char (LHVp) and syngas yield during gasification of municipal solid waste (MSW) during gasification in a fluidized bed reactor. These artificial neural networks (ANNs) with different architectures are trained using the Levenberg-Marquardt (LM) back-propagation algorithm and a cross validation is also performed to ensure that the results generalise to other unseen datasets. A rigorous study is carried out on optimally choosing the number of hidden layers, number of neurons in the hidden layer and activation function in a network using multiple Monte Carlo runs. Nine input and three output parameters are used to train and test various neural network architectures in both multiple output and single output prediction paradigms using the available experimental datasets. The model selection procedure is carried out to ascertain the best network architecture in terms of predictive accuracy. The simulation results show that the ANN based methodology is a viable alternative which can be used to predict the performance of a fluidized bed gasifier.
authors: Carbolea Research Group, Chemical and Environmental Science Department, Bernal Institute, University of Limerick, Ireland.
authors: Daya Shankar
authors: DS
authors: Pandey
authors: Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, United Kingdom.
authors: Saptarshi
authors: S
authors: Das
authors: Department of Earth Science and Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.
authors: Indranil
authors: I
authors: Pan
authors: Carbolea Research Group, Chemical and Environmental Science Department, Bernal Institute, University of Limerick, Ireland.
authors: James J
authors: JJ
authors: Leahy
authors: Carbolea Research Group, Chemical and Environmental Science Department, Bernal Institute, University of Limerick, Ireland. Electronic address: witold.kwapinski@ul.ie.
authors: Witold
authors: W
authors: Kwapinski
keywords: Artificial neural networks; Feed-forward multilayer perceptron; Fluidized bed gasifier; Gasification; Municipal solid waste