Obiekt
Tytuł: A novel Fuzzy C-Regression Model algorithm using a new error measure and particle swarm optimization
Współtwórca:
Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.
Tytuł publikacji grupowej:
Abstract:
This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorith ; Then, particle swarm optimization is employed to finally tune parameters of the obtained fuzzy model. The orthogonal least squares method is used to identify the unknown parameters of the local linear model. Finally, validation results of two examples are given to demonstrate the effectiveness and practicality of the proposed algorithm.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, Volume 22, Number 3 (2012) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Repozytorium > Typy utworów > Artykuły
- Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS)
- Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2012)
Data ostatniej modyfikacji:
2024-11-05
Data dodania obiektu:
2018-09-10
Liczba wyświetleń treści obiektu:
191
Wszystkie dostępne wersje tego obiektu:
https://zbc.uz.zgora.pl/repozytorium/publication/55125
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| Nazwa wydania | Data |
|---|---|
| A novel Fuzzy C-Regression Model algorithm using a new error measure and particle swarm optimization | 2024-11-05 |
