| 학회 |
한국화학공학회 |
| 학술대회 |
2021년 가을 (10/27 ~ 10/29, 광주 김대중컨벤션센터) |
| 권호 |
27권 2호, p.1226 |
| 발표분야 |
[주제별 심포지엄] 그린뉴딜 공정시스템기술 심포지엄-2(공정시스템부문위원회) |
| 제목 |
Hybrid modeling approach to describe uncertain dynamic systems: what we are better than computer scientists |
| 초록 |
Bio-process is difficult to model given its use of living micro-organisms to produce useful products via complex mechanisms. These reactions and their kinetics are hard to characterize; hence, there approximate formulations are used when building a first-principled model. Consequently, such a model will be of poor accuracy. Recently, there is a lot of interest towards data-driven modeling as the amount of data collected, stored, and utilized is growing tremendously due to advent of supercomputing power and gigantic data storage systems. Additionally, data-driven models are simple and easy to build but their utility is hugely restricted by the amount and quality of data used to develop them. Therefore, hybrid modeling is an attractive alternative to purely data-based modeling, wherein it combines a first-principled model with a data-driven model resulting in improved accuracy and robustness. We have successfully validated the developed hybrid modeling approach with two cases case studies: NF-κB signaling pathways and a bio-fermentation reactor. |
| 저자 |
Joseph S. Kwon, Dongheon Lee, Mohammed Saad Faizan Bangi
|
| 소속 |
Texas A&M Univ. |
| 키워드 |
Hybrid modeling; biological process systems
|
| E-Mail |
|
| 원문파일 |
초록 보기 |
