Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network
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...
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Society of Chemical Engineers, Japan
2016
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my.utm.717262017-11-22T12:07:36Z http://eprints.utm.my/id/eprint/71726/ Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network Md. Sarip, M. S. Yamashita, Y. Morad, N. A. Che Yunus, M. A. Abdul Aziz, M. K. T Technology (General) 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. Society of Chemical Engineers, Japan 2016 Article PeerReviewed 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 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978645366&doi=10.1252%2fjcej.15we251&partnerID=40&md5=7d1c0e1b230a7b89fc174600d304b8a0 |
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T Technology (General) Md. Sarip, M. S. Yamashita, Y. Morad, N. A. Che Yunus, M. A. Abdul Aziz, M. K. Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
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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. |
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Article |
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Md. Sarip, M. S. Yamashita, Y. Morad, N. A. Che Yunus, M. A. Abdul Aziz, M. K. |
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Md. Sarip, M. S. Yamashita, Y. Morad, N. A. Che Yunus, M. A. Abdul Aziz, M. K. |
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Md. Sarip, M. S. |
title |
Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
title_short |
Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
title_full |
Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
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Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
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Modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
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modeling and optimization of the hot compressed water extraction of palm oil using artificial neural network |
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Society of Chemical Engineers, Japan |
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2016 |
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http://eprints.utm.my/id/eprint/71726/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978645366&doi=10.1252%2fjcej.15we251&partnerID=40&md5=7d1c0e1b230a7b89fc174600d304b8a0 |
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