Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks

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

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Official URL: https://doi.org/10.1007/s10570-019-02406-z

Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Oil palm fronds; Wavelet neural networks; Response surface methodology; Acetosolv pulping; Environmentally friendly process; Pulp and paper properties
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	Faculty of Mechanical and Manufacturing Engineering > Department of Mechanical Engineering
Depositing User:	Miss Afiqah Faiqah Mohd Hafiz
Date Deposited:	24 Nov 2021 02:18
Last Modified:	24 Nov 2021 02:18
URI:	http://eprints.uthm.edu.my/id/eprint/4065

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