ME 697R Lecture 8.5: Machine Learning Techniques - Prediction of Thermal Properties

By Xiulin Ruan

Mechanical Engineering, Purdue University, West Lafayette, IN

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Researchers should cite this work as follows:

  • Xiulin Ruan (2020), "ME 697R Lecture 8.5: Machine Learning Techniques - Prediction of Thermal Properties," https://nanohub.org/resources/33105.

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2004 Mechanical Engineering, Purdue University, West Lafayette, IN

ME 697R Lecture 8.5: Machine Learning Techniques - Prediction of Thermal Properties
  • Lecture 8.5: Prediction of thermal properties 1. Lecture 8.5: Prediction of the… 0
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  • Machine Learning Potential for Amorphous Materials 2. Machine Learning Potential for… 21.65498832165499
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  • EMD and NEMD Simulations 3. EMD and NEMD Simulations 227.46079412746082
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  • Thermal Interfacial Transport 4. Thermal Interfacial Transport 374.94160827494164
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  • Machine Learning Approach 5. Machine Learning Approach 523.18985652318986
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  • Machine Learning Results 6. Machine Learning Results 645.54554554554556
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  • Using 7. Using "Reliable" Descriptors 733.933933933934
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  • Two-dimensional Composite Materials 8. Two-dimensional Composite Mate… 874.80814147480817
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  • Machine Learning Methods 9. Machine Learning Methods 1004.2375709042376
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  • SVR and GPR Results 10. SVR and GPR Results 1223.6236236236236
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  • CNN Results 11. CNN Results 1378.0447113780447
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