The Yield Prediction of Synthetic Fuel Production from Pyrolysis of Plastic Waste by Levenberg–Marquardt Approach in Feedforward Neural Networks Model

Abnisa, Faisal and Sharuddin, Shafferina Dayana Anuar and Zanil, Mohd Fauzi and Daud, Wan Mohd Ashri Wan and Indra Mahlia, Teuku Meurah (2019) The Yield Prediction of Synthetic Fuel Production from Pyrolysis of Plastic Waste by Levenberg–Marquardt Approach in Feedforward Neural Networks Model. Polymers, 11 (11). p. 1853. ISSN 2073-4360, DOI https://doi.org/10.3390/polym11111853.

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Official URL: https://doi.org/10.3390/polym11111853

Abstract

The conversion of plastic waste into fuel by pyrolysis has been recognized as a potential strategy for commercialization. The amount of plastic waste is basically different for each country which normally refers to non-recycled plastics data; consequently, the production target will also be different. This study attempted to build a model to predict fuel production from different non-recycled plastics data. The predictive model was developed via Levenberg-Marquardt approach in feed-forward neural networks model. The optimal number of hidden neurons was selected based on the lowest total of the mean square error. The proposed model was evaluated using the statistical analysis and graphical presentation for its accuracy and reliability. The results showed that the model was capable to predict product yields from pyrolysis of non-recycled plastics with high accuracy and the output values were strongly correlated with the values in literature. © 2019 by the authors.

Item Type: Article
Funders: Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. (DF-435-829-1441)
Uncontrolled Keywords: plastic waste; pyrolysis; artificial neural network; prediction; fuel
Subjects: T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 08 May 2020 05:09
Last Modified: 08 May 2020 05:09
URI: http://eprints.um.edu.my/id/eprint/24281

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