Thermal conductivity prediction of nano enhanced phase change materials: A comparative machine learning approach

Thermal conductivity prediction of nano enhanced phase change materials: A comparative machine learning approach

Thermal conductivity is one of the crucial properties of nano enhanced phase change materials (NEPCM). Then, in this study three different machine learning methods namely MARS (Multivariate Adaptive Regression Spline), CART (Classification and Regression Tree) and ANN (Artificial Neural Network) is...

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Bibliographic Details
Main Author: Jaliliantabar, F.
Format: Article
Language:English
English
Published: Elsevier Ltd 2022
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/33890/
http://umpir.ump.edu.my/id/eprint/33890/1/Thermal%20conductivity%20prediction%20of%20nano%20enhanced%20phase%20change%20materials.pdf
http://umpir.ump.edu.my/id/eprint/33890/2/Thermal%20conductivity%20prediction%20of%20nano%20enhanced%20phase%20change%20materials_FULL.pdf

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