A review of advanced optimization strategies for fermentative biohydrogen production processes
The inability of statistical optimization to represent the dynamic interaction of the biohydrogen process, which is highly non-linear and complicated, has been identified. However, incorporating a data-driven black-box model could overcome the limitations of conventional methods to provide correct r...
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オンライン・アクセス: | http://ir.unimas.my/id/eprint/38298/1/Mohd%20Asrul%20et%20al.%20%282022%29-1.pdf http://ir.unimas.my/id/eprint/38298/ https://www.sciencedirect.com/science/article/pii/S0360319922013301?dgcid=author https://doi.org/10.1016/j.ijhydene.2022.03.197 |
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my.unimas.ir.382982022-04-13T02:36:28Z http://ir.unimas.my/id/eprint/38298/ A review of advanced optimization strategies for fermentative biohydrogen production processes Mohd Farid, Bin Atan MOHAMAD AFIQ, MOHD ASRUL Hafizah, Abdul Halim Yun Josephine, Chang Hui Lai TD Environmental technology. Sanitary engineering TP Chemical technology The inability of statistical optimization to represent the dynamic interaction of the biohydrogen process, which is highly non-linear and complicated, has been identified. However, incorporating a data-driven black-box model could overcome the limitations of conventional methods to provide correct responses rapidly and cost-effective modeling. Despite significant reports on the optimization of hydrogen production from fermentation, fewer studies have been made for the case using artificial intelligence algorithms. As a result, critical and extensive analyses of previous works are conducted to develop a general methodological framework for advanced response optimization. ELSEVIER 2022-04-12 Article PeerReviewed text en http://ir.unimas.my/id/eprint/38298/1/Mohd%20Asrul%20et%20al.%20%282022%29-1.pdf Mohd Farid, Bin Atan and MOHAMAD AFIQ, MOHD ASRUL and Hafizah, Abdul Halim Yun and Josephine, Chang Hui Lai (2022) A review of advanced optimization strategies for fermentative biohydrogen production processes. International Journal of Hydrogen Energy. pp. 1-20. ISSN 0360-3199 https://www.sciencedirect.com/science/article/pii/S0360319922013301?dgcid=author https://doi.org/10.1016/j.ijhydene.2022.03.197 |
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TD Environmental technology. Sanitary engineering TP Chemical technology Mohd Farid, Bin Atan MOHAMAD AFIQ, MOHD ASRUL Hafizah, Abdul Halim Yun Josephine, Chang Hui Lai A review of advanced optimization strategies for fermentative biohydrogen production processes |
description |
The inability of statistical optimization to represent the dynamic interaction of the biohydrogen process, which is highly non-linear and complicated, has been identified. However, incorporating a data-driven black-box model could overcome the limitations of conventional methods to provide correct responses rapidly and cost-effective modeling. Despite significant reports on the optimization of hydrogen production from fermentation, fewer studies have been made for the case using artificial intelligence algorithms. As a result, critical and extensive analyses of previous works are conducted to develop a general methodological framework for advanced response optimization. |
format |
Article |
author |
Mohd Farid, Bin Atan MOHAMAD AFIQ, MOHD ASRUL Hafizah, Abdul Halim Yun Josephine, Chang Hui Lai |
author_facet |
Mohd Farid, Bin Atan MOHAMAD AFIQ, MOHD ASRUL Hafizah, Abdul Halim Yun Josephine, Chang Hui Lai |
author_sort |
Mohd Farid, Bin Atan |
title |
A review of advanced optimization strategies for fermentative biohydrogen production processes |
title_short |
A review of advanced optimization strategies for fermentative biohydrogen production processes |
title_full |
A review of advanced optimization strategies for fermentative biohydrogen production processes |
title_fullStr |
A review of advanced optimization strategies for fermentative biohydrogen production processes |
title_full_unstemmed |
A review of advanced optimization strategies for fermentative biohydrogen production processes |
title_sort |
review of advanced optimization strategies for fermentative biohydrogen production processes |
publisher |
ELSEVIER |
publishDate |
2022 |
url |
http://ir.unimas.my/id/eprint/38298/1/Mohd%20Asrul%20et%20al.%20%282022%29-1.pdf http://ir.unimas.my/id/eprint/38298/ https://www.sciencedirect.com/science/article/pii/S0360319922013301?dgcid=author https://doi.org/10.1016/j.ijhydene.2022.03.197 |
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1731229843561906176 |
score |
13.250246 |