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A novel data-driven optimization framework for a liquid-only transfer extractive dividing wall column
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DOI:10.1016/j.seppur.2026.139653.png)
Abstract
En 中文
• Gradient information from neural networks generates variable sets. • SHAP analysis is integrated to improve convergence. • The framework is evaluated offline and online. • Multiple independent runs indicate the robustness of the framework.
Journal
IF:
9
Papers:
2.9W
Citations:
12.1W
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