Wavelet neural networks applied to pulping of oil palm fronds

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

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Organosolv; Palm fronds; Pulping; Response surface methodology; Wavelet neural networks
Subjects:	T Technology > TS Manufactures > TS1080-1268 Paper manufacture and trade
Divisions:	Faculty of Mechanical and Manufacturing Engineering > Department of Mechanical Engineering
Depositing User:	Miss Nur Rasyidah Rosli
Date Deposited:	01 Dec 2021 06:31
Last Modified:	01 Dec 2021 06:31
URI:	http://eprints.uthm.edu.my/id/eprint/4224

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