International Journal of Media and Networks(IJMN)
ISSN: 2995-3286 | DOI: 10.33140/IJMN
Impact Factor: 1.02
Abhilash Akula
Saint Louis University, St. Louis, MO, USA
Publications
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Review Article
Predict Unknown Properties of Elements of Periodic Table with Machine Learning
Author(s): Yash K. Bhatia, Maxwell Gao, Sruthi Ainapurapu, Abhilash Akula, Elizabeth A. Christophy, Payam Norouzzadeh, Steven Buckner and Bahareh Rahmani*
The periodic table of elements includes 92 elements with many unknown properties like melting point, boiling point, heat of vaporization, and molar heat capacity of some specific elements such as Curium, Berkelium, Californium, and Einsteinium. Physicists, chemists, and other scientists have done many successful experiments to predict these mysterious features using the first principal methods. But still many properties have been unclear. In this project we apply Machine Learning models such as linear and logistic regression to predict this unknow values. The known values split to train and test data to find and confirm the model. Then the model will be run over unknown variables... Read More»