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Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis
In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7701202/ https://www.ncbi.nlm.nih.gov/pubmed/33294718 http://dx.doi.org/10.1016/j.heliyon.2020.e05598 |
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author | Pan, Ruming Duque, João Vitor Ferreira Martins, Márcio Ferreira Debenest, Gérald |
author_facet | Pan, Ruming Duque, João Vitor Ferreira Martins, Márcio Ferreira Debenest, Gérald |
author_sort | Pan, Ruming |
collection | PubMed |
description | In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 °C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390–510 °C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~ 1) and pyrolysis rates (> 0.999), and the waste PE conversions (~ 1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results. |
format | Online Article Text |
id | pubmed-7701202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-77012022020-12-07 Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis Pan, Ruming Duque, João Vitor Ferreira Martins, Márcio Ferreira Debenest, Gérald Heliyon Research Article In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 °C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390–510 °C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~ 1) and pyrolysis rates (> 0.999), and the waste PE conversions (~ 1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results. Elsevier 2020-11-25 /pmc/articles/PMC7701202/ /pubmed/33294718 http://dx.doi.org/10.1016/j.heliyon.2020.e05598 Text en © 2020 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Pan, Ruming Duque, João Vitor Ferreira Martins, Márcio Ferreira Debenest, Gérald Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title | Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title_full | Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title_fullStr | Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title_full_unstemmed | Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title_short | Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
title_sort | application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7701202/ https://www.ncbi.nlm.nih.gov/pubmed/33294718 http://dx.doi.org/10.1016/j.heliyon.2020.e05598 |
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