Md. Sarip, M. S. and Yamashita, Y. and Morad, N. A. and Che Yunus, M. A. and Abdul Aziz, M. K. (2016) Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network. Journal of Chemical Engineering of Japan, 49 (7). pp. 614-621. ISSN 0021-9592
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Abstract
Hot compressed water extraction (HCWE) is a promising green alternative to the screw press in the palm oil processing. In this study, the steady-state characteristic of the HCWE was modeled by using an artificial neural network (ANN). The overall oil yield and other outputs; β-carotene, α-tocopherol and α-tocotrienol concentration, were described by the pressure and temperature in the HCWE. The results show that the predicted yield and concentrations agree well with experimental data. These models were used to estimate the optimum conditions of the HCWE process.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Neural networks, Oil shale, Palm oil, Water, Beta carotene, Hot compressed water, Modeling and optimization, Oil processing, Optimum conditions, Predicted yield, Pressure and temperature, Steady state characteristics, Extraction |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Malaysia-Japan International Institute of Technology |
| ID Code: | 71726 |
| Deposited By: | Widya Wahid |
| Deposited On: | 22 Nov 2017 12:07 |
| Last Modified: | 22 Nov 2017 12:07 |
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