Publication detail

Comparing of Evolutionary and Non-parametric Algorithms and Data Preparing

SVĚTLÍK, M.

Original Title

Comparing of Evolutionary and Non-parametric Algorithms and Data Preparing

Type

conference paper

Language

English

Original Abstract

This paper deals with modern approaches for electrical machine designing and data preparation for these methods. The discussed methods are the genetic algorithm, an algorithm from a group of evolutionary algorithms, and a decision tree, which belongs to non-parametric algorithms. This paper describes the genetic algorithm’s main benefits, robustness, and high precision. Moreover, decision tree benefits like low computing time or low requirements for computing power are also discussed. Mathematical filters used for data preparation are necessary for reaching high accuracy of calculations. Bad chosen or used filters can lead to higher computing power requirements or increased computing time.

Keywords

Decision tree, Genetic algorithm, mathematical filters

Authors

SVĚTLÍK, M.

Released

25. 4. 2023

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-6153-6

Book

Proceedings I of the 29th Student EEICT 2023 (General Papers)

Edition

1

Pages from

322

Pages to

326

Pages count

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf

BibTex

@inproceedings{BUT184029,
  author="Martin {Světlík}",
  title="Comparing of Evolutionary and Non-parametric Algorithms and Data Preparing",
  booktitle="Proceedings I of the 29th Student EEICT 2023 (General Papers)",
  year="2023",
  series="1",
  pages="322--326",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6153-6",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf"
}