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September 27, 2024MaterialsOpen Access

Predictions of Lattice Parameters in NiTi High-Entropy Shape-Memory Alloys Using Different Machine Learning Models

Tu‐Ngoc Lam Jiajun Jiang Min-Cheng Hsu Shr-Ruei Tsai Mao-Yuan Luo Shuo-Ting Hsu Wen‐Jay Lee Chung‐Hao Chen E‐Wen Huang

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Abstract

This work applied three machine learning (ML) models-linear regression (LR), random forest (RF), and support vector regression (SVR)-to predict the lattice parameters of the monoclinic B19' phase in two distinct training datasets: previously published ZrO

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Cite This Study

Lam et al. (2024) studied this question.

synapsesocial.com/papers/68e572c8b6db643587513191 https://doi.org/10.3390/ma17194754

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