Evolutionary data driven modeling and tri-objective optimization for noisy BOF steel making data
Evolutionary data-driven modeling and optimization play a major role in generating meta models from real-time data. These surrogate models are applied effectively in various industrial operations and processes to predict a more accurate model from the nonlinear and noisy data. In this work, the data...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-06-01
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| Series: | Digital Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772508123000121 |