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| 机器学习在轮胎配方设计中的应用 |
| Application of Machine Learning in Tire Formula Design |
| Received:July 17, 2024 Revised:July 17, 2024 |
| DOI：10.12135/j.issn.1006-8171.2025.09.0515 |
| 中文关键词: 轮胎；配方设计；机器学习；主成分分析；数据挖掘 |
| 英文关键词: tire；formula design；machine learning；principal component analysis；data mining |
| 基金项目: |
| 中图分类号: |
| Author Name | Affiliation | E-mail | | ZHAO Jianming* | 上海轮胎研究所有限公司 | zhaojianming@shhuayi.com | | LU Tian | 数之微信息科技有限公司 | | | LI Minjie | 上海大学 | | | LU Wencong | 上海大学 | |
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| 中文摘要: |
| 探索机器学习在轮胎配方设计中的应用。结果表明：可以利用数据挖掘的方法进行配方设计中单个性能的优化，对其他重点指标，可以增加1个分类指标进行控制，从而达到性能优化的目标；可以利用聚类原则进行配方优化，但该原则仅代表取得较好性能的概率较大，并非选取的优化点肯定都好。 |
| 英文摘要: |
| The application of machine learning in tire formula design was explored.The results indicated that data mining methods could be used to optimize individual performance in formula design，and an additional classification indicator could be added to control other key indicators，thereby achieving the goal of performance optimization.The clustering principle could be used for formula optimization，but this principle only represented a high probability of achieving good performance，and not all selected optimization points were necessarily good. |
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