Journal of Modern Research Physics
Volume 10, Issue 2 (Autumn and Winter 2026)
JMRPh 2026, 10(2): 18-25 |
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Ghaffaripour A, Vaseghi B. Efficient machine learning method, Stacking, to improvement of material band gaps prediction. JMRPh 2026; 10 (2) :18-25
URL: http://jmrph.khu.ac.ir/article-1-285-en.html
URL: http://jmrph.khu.ac.ir/article-1-285-en.html
Yasouj University
Abstract: (250 Views)
In this research, energy band gap of specific materials has been predicted using machine learning approach. We try by using mixing some usual machine learning methods to presenting an efficient machine learning method to improve material band gap prediction. Based on Gradient Boosting Decision Tree, Light Gradient Boosting, Random Forest and Extreme Gradient Boosting, we presented Stacking method by mixing all mentioned methods as an efficient machine learning method.
Type of Study: Research |
Received: 2026/01/19 | Accepted: 2026/02/8 | Published: 2026/03/20 | ePublished: 2026/03/20
Received: 2026/01/19 | Accepted: 2026/02/8 | Published: 2026/03/20 | ePublished: 2026/03/20
References
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