Detail publikace

Comparative Analysis of Gaussian Process Regression Modeling of an Induction Machine: Continuous vs. Mixed-Input Approaches

BÍLEK, V.

Originální název

Comparative Analysis of Gaussian Process Regression Modeling of an Induction Machine: Continuous vs. Mixed-Input Approaches

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper investigates the application of machine learning technique for modeling continuous and mixed-input parameters of electrical machines. The design of electrical machines typically requires the consideration of certain parameters as integer values due to their physical significance, including the number of stator/rotor slots, stator wires, and rotor bars. Traditional machine learning methods, which predominantly treat input parameters as purely continuous, may compromise modeling accuracy for such applications. To address this challenge, models capable of handling mixed-input parameters were used for the case study. Two training datasets were generated: one with purely continuous inputs and another with both continuous inputs and a categorical parameter, specifically, the number of stator conductors. Gaussian process regression was employed to build three models: two with continuous kernels, trained on both datasets, and one with a mixed kernel, trained only on the dataset containing a categorical parameter. A comparative analysis, demonstrated on a 1.5 kW induction machine - though applicable to a wide range of machines - illustrates the differences between the proposed approaches. The results highlight the importance of selecting an appropriate model for the Multi-Objective Bayesian optimization of electrical machines.

Klíčová slova

Finite element method, Gaussian process regression, Induction machine, Machine learning, Mixed-Input surrogate models, Surrogate modeling

Autoři

BÍLEK, V.

Vydáno

23. 4. 2024

Nakladatel

Brno University of Technology, Faculty of Elektronic Engineering and Communication

Místo

Brno

ISBN

978-80-214-6230-4

Kniha

PROCEEDINGS II OF THE 30TH STUDENT EEICT 2024 Selected papers

Edice

1

Strany od

227

Strany do

231

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_2.pdf

BibTex

@inproceedings{BUT188911,
  author="Vladimír {Bílek}",
  title="Comparative Analysis of Gaussian Process Regression Modeling of an Induction Machine: Continuous vs. Mixed-Input Approaches",
  booktitle="PROCEEDINGS II OF THE 30TH STUDENT EEICT 2024 Selected papers",
  year="2024",
  series="1",
  pages="227--231",
  publisher="Brno University of Technology, Faculty of Elektronic Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6230-4",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_2.pdf"
}