Endpoint carbon content and temperature prediction model in BOF steelmaking based on posterior probability and intra-cluster feature weight online dynamic feature selection
A posterior probability and intra-cluster feature weight online dynamic feature selection algorithm is proposed to address the issues of high dimensionality and high volatility of data in the basic oxygen furnace (BOF) steelmaking production process. First, a genetic algorithm with fixed feature spa...
Tallennettuna:
| Päätekijät: | , , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
De Gruyter
2025-01-01
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| Sarja: | High Temperature Materials and Processes |
| Aiheet: | |
| Linkit: | https://doi.org/10.1515/htmp-2024-0067 |
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