Predicting Plasma Temperature From Line Intensities Using ML Models
Plasma Physics
2025-05-05 v1
Abstract
In this work, ML models were used to predict the plasma temperature using the dataset obtained by implementing the CR-model for Na-like Krypton. The models included in the study are: Linear Regression, Lasso Regression, Support Vector Regression, Decision Trees, Random Forest, XGBoost, Multi-layer Perceptron and Convolutional Neural Network. For evaluating the models we used Mean Absolute Error, Mean Squared Error and R^2 Score as metrics, In our study Random Forest performed best as compared to other model considered, the study conclude that complex relation between the line-intensities and Plasma temperature can be capture by ML models and they can be used to predict the temperature with high accuracy.
Cite
@article{arxiv.2505.01414,
title = {Predicting Plasma Temperature From Line Intensities Using ML Models},
author = {Ashwini Malviya},
journal= {arXiv preprint arXiv:2505.01414},
year = {2025}
}