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基于多响应优化和基于机器学习的预测,可以对AZ31合金的直槽热增量板形成进行预测

Amar A Khot1, Rohit A Magdum2, Anjali R Magdum3

  • 1Department of Mechanical Engineering, Sharad Institute of Technology College of Engineering, Yadrav, Maharashtra, 416115, India.

Scientific reports
|January 27, 2026
PubMed
概括

这项研究优化了AZ31合金的热增量板成型 (ISF). 它发现温度和下降显著影响形成,机器学习提高了有效生产的预测准确性.

关键词:
合金AZ31合金形成的力量是形成的力量.渐进式板材成型 渐进式板材成型机器学习 机器学习多响应优化多响应优化随机的森林随机的森林这里是TOPSIS的地图.塔古奇的方法 塔古奇方法温暖的形成形成.

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