Database

Published: 25 July 2025| Version 1 | DOI: 10.17632/9ks6z77wsd.1
Contributors:
Irina Medyankina,
,

Description

The programs were developed using Python 3.11.1 and libraries Tensorflow v 2.13.0, Scikit-learn v 1.2.2 and Matplotlib v3.6.2. Python can be installed from the website https://www.python.org/. To install libraries, you need to enter the following commands in the command line: pip install tensorflow==2.13.0 pip install scikit-learn==1.2.2 pip install matplotlib==3.6.2 We trained three models: Artificial Neural Networks (ANN), Linear Least Squares (LS) regression and Random Forest Regressor (RF). The file with the model training has the name «* _learning.py» and the results visualization file «*_3D_plot.py» To run the ANN_3D_plot.py two files are required: tf_model.keras – contains a learning model; training_history.json – contains training history

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Institutions

  • FGBUN Institut himii tverdogo tela Ural'skogo otdelenia Rossijskoj akademii nauk Laboratoria oksidnyh sistem

Categories

Physical Chemistry, Mathematical Modeling for Materials Science, Data Processing, Artificial Intelligence Model

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