Open AccessUsing Physical Parameters for Phase Prediction of Multi-Component Alloys by the Help of TensorFlow Machine Learning with Limited DataUsing Physical Parameters for Phase Prediction of Multi-Component Alloys by the Help of TensorFlow Machine Learning with Limited Data
Author(s) -
Kağan Şarlar
Publication year - 2021
Publication title -
sakarya üniversitesi fen bilimleri enstitüsü dergisi/sakarya üniversitesi fen bilimleri enstitüsü dergisi
Language(s) - English
Resource type - Journals
eISSN - 2147-835X
pISSN - 1301-4048
DOI - 10.16984/saufenbilder.840548
Subject(s) - electronegativity , artificial intelligence , component (thermodynamics) , machine learning , computer science , alloy , high entropy alloys , valence (chemistry) , thermodynamics , materials science , chemistry , physics , metallurgy , organic chemistry