Temat: grupowanie nienadzorowane - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Generalized fuzzy clustering method
Autorzy:: Przybyła, T.
Roj, D.
Jeżewski, J.
Matonia, A.
Powiązania:: https://bibliotekanauki.pl/articles/332927.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: grupowanie rozmyte
uogólniona funkcja kosztów
grupowanie nienadzorowane
fuzzy clustering
fuzzy meridian
fuzzy myriad
generalized cost function
unsupervised clustering
Opis:: This paper presents a new hybrid fuzzy clustering method. In the proposed method, cluster prototypes are values that minimize the introduced generalized cost function. The proposed method can be considered as a generalization of fuzzy c–means (FCM) method as well as the fuzzy c–median (FCMed) clustering method. The generalization of the cluster cost function is made by applying the Lp norm. The values that minimize the proposed cost function have been chosen as the group prototypes. The weighted myriad is the special case of the group prototype, when the Lp norm is the L2 (Euclidean) norm. The cluster prototypes are the weighted meridians for the L1 norm. Artificial data set is used to demonstrate the performance of proposed method.
Źródło:: Journal of Medical Informatics & Technologies; 2010, 16; 69-76
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Application of unsupervised learning algorithms for analysis the vibrations of an oscillator forced by a random series of impulses
Autorzy:: Ozga, Agnieszka
Sulewski, Marek
Powiązania:: https://bibliotekanauki.pl/articles/24201982.pdf
Data publikacji:: 2023
Wydawca:: Politechnika Poznańska. Instytut Mechaniki Stosowanej
Tematy:: machine learning
stochastic series of impulses
unsupervised machine learning
hierarchical clustering
uczenie maszynowe
losowa seria impulsów
uczenie nienadzorowane
grupowanie hierarchiczne
Opis:: Paper discusses a mathematical model describing the vibrations of a linear oscillator forced by a random series of impulses. The study aims at checking how precisely the distributions of values of the impulses forcing the vibrations of an oscillator can be differentiated. The analysis was carried out in the MatLab environment with the use of hierarchical clustering algorithms of unsupervised machine learning, for samples generated from computer simulation. The time series are non-stationary. The studies showed that high precision could be achieved in distinguishing two very similar distributions forcing the vibrations, on the basis of an analysis of the two first moments calculated from the movement.
Źródło:: Vibrations in Physical Systems; 2023, 34, 1; art. no. 2023121
0860-6897
Pojawia się w:: Vibrations in Physical Systems
Dostawca treści:: Biblioteka Nauki

Artykuł

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