IMPLEMENTING OF MICROSOFT AZURE MACHINE LEARNING TECHNOLOGY FOR ELECTRIC MACHINES OPTIMIZATION

Authors

  • V. E. Pliugin O.M. Beketov National University of Urban Economy in Kharkiv, Ukraine https://orcid.org/0000-0003-4056-9771
  • M. Sukhonos O.M. Beketov National University of Urban Economy in Kharkiv, Ukraine https://orcid.org/0000-0002-7246-8740
  • M. Pan O.M. Beketov National University of Urban Economy in Kharkiv, Ukraine
  • A. N. Petrenko O.M. Beketov National University of Urban Economy in Kharkiv, Ukraine
  • N. Ya. Petrenko National Technical University «Kharkiv Polytechnic Institute», Ukraine

DOI:

https://doi.org/10.20998/2074-272X.2019.1.04

Keywords:

electrical machines, optimization, algorithm, data set, machine learning, Microsoft Azure, cloud computing

Abstract

Purpose. To consider problems of electric machines optimization within a wide range of many variables variation as well as the presence of many calculation constraints in a single-criteria optimization search tasks. Results. A structural model for optimizing electric machines of arbitrary type using Microsoft Azure machine learning technology has been developed. The obtained results, using several optimization methods from the Microsoft Azure database are demonstrated. The advantages of cloud computing and optimization based on remote servers are shown. The results of statistical analysis of the results are given. Originality. Microsoft Azure machine learning technology was used for electrical machines optimization for the first time. Recommendations for modifying standard algorithms, offered by Microsoft Azure are given. Practical value. Significant time reduction and resources spent on the optimization of electrical machines in a wide range of variable variables. Reducing the time to develop optimization algorithms. The possibility of automatic statistical analysis of the results after performing optimization calculations. 

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Published

2019-02-17

How to Cite

Pliugin, V. E., Sukhonos, M., Pan, M., Petrenko, A. N., & Petrenko, N. Y. (2019). IMPLEMENTING OF MICROSOFT AZURE MACHINE LEARNING TECHNOLOGY FOR ELECTRIC MACHINES OPTIMIZATION. Electrical Engineering & Electromechanics, (1), 23–28. https://doi.org/10.20998/2074-272X.2019.1.04

Issue

No. 1 (2019)

Section

Electrical Machines and Apparatus

License

Copyright (c) 2019 V. E. Pliugin, M. Sukhonos, M. Pan, A. N. Petrenko, N. Ya. Petrenko

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