Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms
Chemical activation; Gasification; Learning algorithms; Machine learning; Multilayer neural networks; Neurons; Plastics industry; Predictive analytics; Rubber; Rubber industry; Activation functions; MLP neural networks; Model architecture; Multi layer perceptron; Neural network algorithm; Optimized...
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John Wiley and Sons Ltd
2023
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| author | Ayodele B.V. Mustapa S.I. Kanthasamy R. Zwawi M. Cheng C.K. |
| author2 | 56862160400 |
| author_facet | 56862160400 Ayodele B.V. Mustapa S.I. Kanthasamy R. Zwawi M. Cheng C.K. |
| author_sort | Ayodele B.V. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Chemical activation; Gasification; Learning algorithms; Machine learning; Multilayer neural networks; Neurons; Plastics industry; Predictive analytics; Rubber; Rubber industry; Activation functions; MLP neural networks; Model architecture; Multi layer perceptron; Neural network algorithm; Optimized performance; Process operation; Radial Basis Function(RBF); Hydrogen production |
| format | Article |
| id | my.uniten.dspace-26232 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | John Wiley and Sons Ltd |
| record_format | dspace |
| spelling | my.uniten.dspace-262322023-05-29T17:08:03Z Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms Ayodele B.V. Mustapa S.I. Kanthasamy R. Zwawi M. Cheng C.K. 56862160400 36651549700 56070146400 56584631800 57204938666 Chemical activation; Gasification; Learning algorithms; Machine learning; Multilayer neural networks; Neurons; Plastics industry; Predictive analytics; Rubber; Rubber industry; Activation functions; MLP neural networks; Model architecture; Multi layer perceptron; Neural network algorithm; Optimized performance; Process operation; Radial Basis Function(RBF); Hydrogen production This study aimed to investigate the application of radial basis function (RBF) and multilayer perceptron (MLP) artificial neural networks for modeling hydrogen production by co-gasification of rubber and plastic wastes. Both the RBF and MLP neural networks were configured by determining the best-hidden neurons that could offer optimized performance. Based on the best-hidden neurons, a model architecture of 4-16-1, 4-20-1, 4-17-1, and 4-3-1 was obtained for RBF (with standard activation function), RBF (with ordinary activation function), one-layer MLP, and two-layer MLP, respectively, indicating the number of input nodes, the hidden neurons, and the output nodes. The predicted hydrogen production from the co-gasification closely agrees with the observed values. The 1-layer MLP with R2 of.990 displayed the best performance with all the input parameters having a significant influence on 9 the model output. The neural network algorithm obtained in this study could be implemented in the eventuality of making a vital decision in the process operation of the co-gasification process for hydrogen production. � 2021 John Wiley & Sons Ltd Final 2023-05-29T09:08:03Z 2023-05-29T09:08:03Z 2021 Article 10.1002/er.6483 2-s2.0-85100098854 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100098854&doi=10.1002%2fer.6483&partnerID=40&md5=f43ef6221e18dfe69f3057bec8f916b5 https://irepository.uniten.edu.my/handle/123456789/26232 45 6 9580 9594 John Wiley and Sons Ltd Scopus |
| spellingShingle | Ayodele B.V. Mustapa S.I. Kanthasamy R. Zwawi M. Cheng C.K. Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title | Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title_full | Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title_fullStr | Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title_full_unstemmed | Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title_short | Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| title_sort | modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms |
| url_provider | http://dspace.uniten.edu.my/ |