Wavelet neural networks applied to pulping of oil palm fronds
In the organosolv pulping of the oil palm fronds, the influence of the operational variables of the pulping reactor (viz. cooking temperature and time, ethanol and NaOH concentration) on the properties of the resulting pulp (yield and kappa number) and paper sheets (tensile index and tear index) was...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2011
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| Online Access: | http://eprints.uthm.edu.my/4224/ http://eprints.uthm.edu.my/4224/1/AJ%202017%20%28583%29.pdf |
| _version_ | 1848888229399363584 |
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| author | Zainuddin, Zarita Wan Daud, Wan Rosli Pauline, Ong Shafie, Amran |
| author_facet | Zainuddin, Zarita Wan Daud, Wan Rosli Pauline, Ong Shafie, Amran |
| author_sort | Zainuddin, Zarita |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | In the organosolv pulping of the oil palm fronds, the influence of the operational variables of the pulping reactor (viz. cooking temperature and time, ethanol and NaOH concentration) on the properties of the resulting pulp (yield and kappa number) and paper sheets (tensile index and tear index) was investigated using a wavelet neural network model. The experimental results with error less than 0.0965 (in terms of MSE) were produced, and were then compared with those obtained from the response surface methodology. Performance assessment indicated that the neural network model possessed superior predictive ability than the polynomial model, since a very close agreement between the experimental and the predicted values was obtained. |
| first_indexed | 2025-11-15T20:06:58Z |
| format | Article |
| id | uthm-4224 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:06:58Z |
| publishDate | 2011 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-42242021-12-01T06:31:24Z http://eprints.uthm.edu.my/4224/ Wavelet neural networks applied to pulping of oil palm fronds Zainuddin, Zarita Wan Daud, Wan Rosli Pauline, Ong Shafie, Amran TS1080-1268 Paper manufacture and trade In the organosolv pulping of the oil palm fronds, the influence of the operational variables of the pulping reactor (viz. cooking temperature and time, ethanol and NaOH concentration) on the properties of the resulting pulp (yield and kappa number) and paper sheets (tensile index and tear index) was investigated using a wavelet neural network model. The experimental results with error less than 0.0965 (in terms of MSE) were produced, and were then compared with those obtained from the response surface methodology. Performance assessment indicated that the neural network model possessed superior predictive ability than the polynomial model, since a very close agreement between the experimental and the predicted values was obtained. Elsevier 2011 Article PeerReviewed text en http://eprints.uthm.edu.my/4224/1/AJ%202017%20%28583%29.pdf Zainuddin, Zarita and Wan Daud, Wan Rosli and Pauline, Ong and Shafie, Amran (2011) Wavelet neural networks applied to pulping of oil palm fronds. Bioresource Technology, 102 (23). pp. 10978-10986. ISSN 0960-8524 https://doi.org/10.1016/j.biortech.2011.09.080 |
| spellingShingle | TS1080-1268 Paper manufacture and trade Zainuddin, Zarita Wan Daud, Wan Rosli Pauline, Ong Shafie, Amran Wavelet neural networks applied to pulping of oil palm fronds |
| title | Wavelet neural networks applied to pulping of oil palm fronds |
| title_full | Wavelet neural networks applied to pulping of oil palm fronds |
| title_fullStr | Wavelet neural networks applied to pulping of oil palm fronds |
| title_full_unstemmed | Wavelet neural networks applied to pulping of oil palm fronds |
| title_short | Wavelet neural networks applied to pulping of oil palm fronds |
| title_sort | wavelet neural networks applied to pulping of oil palm fronds |
| topic | TS1080-1268 Paper manufacture and trade |
| url | http://eprints.uthm.edu.my/4224/ http://eprints.uthm.edu.my/4224/ http://eprints.uthm.edu.my/4224/1/AJ%202017%20%28583%29.pdf |