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Updated: Sep 18, 2025

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation
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Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation

Published on: May 2, 2016

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基于XGBoost的电热性质建模:BCZT电陶中的贝叶斯优化

Mustafa Cagri Bayir1,2, Ebru Mensur1

  • 1Department of Materials Science and Engineering, Gebze Technical University, 41400 Kocaeli, Türkiye.

Materials (Basel, Switzerland)
|June 27, 2025
PubMed
概括

无电热陶显示出对固态冷却的承诺. 机器学习准确地预测了它们的性能,优化了组合和处理以提高温度变化.

关键词:
在XGBoost中使用.这是一种电热的电热.电陶的电陶是如何使用的优化的优化优化优化.处理 处理 处理 处理这是一个回归回归的回归.

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