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Updated: Jan 7, 2026

Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches
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Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches

Published on: July 22, 2025

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机器学习和深度学习架构的全面框架,具有超启发式优化,用于对纳米流体特定热容量的高可靠性预测

Priya Mathur1, Dheeraj Kumar2, Farhan Sheth2

  • 1Poornima Institute of Engineering and Technology, Jaipur, Rajasthan, India.

Scientific reports
|December 27, 2025
PubMed
概括

预测纳米流体的特定热容量对工业至关重要. 这项研究表明,通过数据增强和优化增强的堆叠机器学习模型,可以实现高度准确的预测,改善传热应用.

关键词:
深度学习是一种深度学习.机器学习 机器学习超启发式优化优化方法纳米流体 纳米流体具体的热容量 具体的热容量热物理性质是一种热物理性质.

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