Detail publikace

Comparing of Evolutionary and Non-parametric Algorithms and Data Preparing

SVĚTLÍK, M.

Originální název

Comparing of Evolutionary and Non-parametric Algorithms and Data Preparing

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Decision tree, Genetic algorithm, mathematical filters

Autoři

SVĚTLÍK, M.

Vydáno

25. 4. 2023

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno

ISBN

978-80-214-6153-6

Kniha

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

Edice

1

Strany od

322

Strany do

326

Strany počet

5

URL

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"
}