Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks
Mathematical models based on response surface methodology (RSM) and wavelet neural networks (WNNs) in conjunction with a central composite design were developed in order to study the influence of pulping variables viz. acetic acid, temperature, time, and hydrochloric acid (catalyst) on the resulting...
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| Format: | Article |
| Language: | en |
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2019
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| Online Access: | http://eprints.uthm.edu.my/4065/1/AJ%202019%20%28207%29.pdf http://eprints.uthm.edu.my/4065/ https://doi.org/10.1007/s10570-019-02406-z |
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| _version_ | 1833417500408152064 |
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| author | Razali, Nasrullah Ong, Pauline Ibrahim, Mazlan Wan Daud, Wan Rosli Zainuddin, Zarita |
| author_facet | Razali, Nasrullah Ong, Pauline Ibrahim, Mazlan Wan Daud, Wan Rosli Zainuddin, Zarita |
| author_sort | Razali, Nasrullah |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Mathematical models based on response surface methodology (RSM) and wavelet neural networks (WNNs) in conjunction with a central composite design were developed in order to study the influence of pulping variables viz. acetic acid, temperature, time, and hydrochloric acid (catalyst) on the resulting pulp and paper properties (screened yield, kappa number, tensile and tear indices) during the acetosolv pulping of oil palm fronds. The performance analysis demonstrated the superiority of WNNs over RSM, in that the former reproduced the experimental results with percentage errors and mean squared errors between 3 and 8% and 0.0054–0.4514 respectively, which were much lower than those obtained by the RSM models with corresponding values of 12–40% and 0.0809–9.3044, further corroborating the goodness of fit of the WNNs models for simulating the acetosolv pulping of oil palm fronds. Based on this assessment, it validates the exceptional predictive ability of the WNNs in comparison to the RSM polynomial model. |
| format | Article |
| id | my.uthm.eprints-4065 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2019 |
| publisher | Springer |
| record_format | eprints |
| spelling | my.uthm.eprints-40652021-11-24T02:18:45Z http://eprints.uthm.edu.my/4065/ Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks Razali, Nasrullah Ong, Pauline Ibrahim, Mazlan Wan Daud, Wan Rosli Zainuddin, Zarita QA273-280 Probabilities. Mathematical statistics Mathematical models based on response surface methodology (RSM) and wavelet neural networks (WNNs) in conjunction with a central composite design were developed in order to study the influence of pulping variables viz. acetic acid, temperature, time, and hydrochloric acid (catalyst) on the resulting pulp and paper properties (screened yield, kappa number, tensile and tear indices) during the acetosolv pulping of oil palm fronds. The performance analysis demonstrated the superiority of WNNs over RSM, in that the former reproduced the experimental results with percentage errors and mean squared errors between 3 and 8% and 0.0054–0.4514 respectively, which were much lower than those obtained by the RSM models with corresponding values of 12–40% and 0.0809–9.3044, further corroborating the goodness of fit of the WNNs models for simulating the acetosolv pulping of oil palm fronds. Based on this assessment, it validates the exceptional predictive ability of the WNNs in comparison to the RSM polynomial model. Springer 2019 Article PeerReviewed text en http://eprints.uthm.edu.my/4065/1/AJ%202019%20%28207%29.pdf Razali, Nasrullah and Ong, Pauline and Ibrahim, Mazlan and Wan Daud, Wan Rosli and Zainuddin, Zarita (2019) Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks. Cellulose, 26. pp. 4615-4628. ISSN 0969-0239 https://doi.org/10.1007/s10570-019-02406-z |
| spellingShingle | QA273-280 Probabilities. Mathematical statistics Razali, Nasrullah Ong, Pauline Ibrahim, Mazlan Wan Daud, Wan Rosli Zainuddin, Zarita Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title | Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title_full | Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title_fullStr | Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title_full_unstemmed | Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title_short | Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| title_sort | modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks |
| topic | QA273-280 Probabilities. Mathematical statistics |
| url | http://eprints.uthm.edu.my/4065/1/AJ%202019%20%28207%29.pdf http://eprints.uthm.edu.my/4065/ https://doi.org/10.1007/s10570-019-02406-z |
| url_provider | http://eprints.uthm.edu.my/ |