Application of Machine Learning Algorithms in Decision Making of State Enterprises

Authors

  • Dženan Šašić International Burch University
  • Zerina Mašetić International Burch University

DOI:

https://doi.org/10.53028/1986-6127.2022.13.1.11

Keywords:

European Union, linear regression, random forest, support vector machine, renewable sources, model, machine learning, datasets

Abstract

One of the conditions that Bosnia and Herzegovina needs to meet in order to become a member of the European Union is to increase the share of electricity production from renewable sources. The aim of this paper is to use a Linear Regression algorithm, Support Vector Machine algorithm and Random Forest algorithm to make a contribution in this area from the aspect of machine learning - more precisely to determine the parameters that most affect the wind speed in Mostar region. The obtained model showed that parameter that most affects the wind speed in Mostar are short-term wind accelerations. The model can be easily generalized and applicable to other data sets.

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Published

2022-06-17

How to Cite

Šašić, D. ., & Mašetić, Z. . (2022). Application of Machine Learning Algorithms in Decision Making of State Enterprises. Uprava, 13(1), 11–16. https://doi.org/10.53028/1986-6127.2022.13.1.11

Issue

Section

Articles