Szczegóły publikacji
Opis bibliograficzny
Application of the forest classifier method for description of movements of an oscillator forced by a stochastic series of impulses / Marek SULEWSKI, Agnieszka OZGA // Journal of Theoretical and Applied Mechanics ; ISSN 1429-2955. — 2023 — vol. 61 nr 4, s. 819–831. — Bibliogr. s. 829–831, Abstr. — W PDF podano błędną numerację stron. --- Publikacja dostępna online od: 2023-10-18
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 149977 |
|---|---|
| Data dodania do BaDAP | 2023-12-06 |
| Tekst źródłowy | URL |
| DOI | 10.15632/jtam-pl/172966 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Theoretical and Applied Mechanics |
Abstract
The article discusses the analysis of motion of an oscillator forced by a sequence of stochastic impulses with the use of decision tree algorithms and a random forest classifier. The aim of this paper is to verify the accuracy of distinguishing distributions in the desired time period and to check whether the length of the time interval affects the accuracy of data classification. Moreover, the statistical parameters directly influencing classification of distributions are presented. The analysis has been performed in Python environment, the data were obtained in computer simulation. The results of classification for two classification algorithms with regard to two divisions of the test and training set sizes are presented. In case of the decision tree classifier, it has been observed that for each time interval this algorithm classifies the data achieving a high level of accuracy, but for the purpose of data classification for each time period it selects different statistics, which makes it impossible to unequivocally determine which statistic influences the recognition of distribution. In case of the random forest classification algorithm, the importance and influence of the parameters on the distribution between the three distributions are the same both in 5-minute and 10-minute intervals. The differences between significance of the parameters depending on length of the interval are not significant.