Obiekt
Tytuł: Data-driven models for fault detection using kernel PCA: A water distribution system case study
Współtwórca:
Cordón, Oskar - ed. ; Kazienko, Przemysław - ed.
Podtytuł:
Hybrid and Ensemble Methods in Machine Learning
Tytuł publikacji grupowej:
Abstract:
Kernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). ; This model is utilised for fault detection with the emphasis on water leakage detection. A systematic description of the system?s framework is followed by evaluation of its performance. Simulations prove that the presented approach is both flexible and efficient.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, Volume 22, Number 4 (2012) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Typy utworów > Artykuły
- Zielonogórska Biblioteka Cyfrowa > 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:
2021-10-14
Data dodania obiektu:
2021-09-15
Liczba wyświetleń treści obiektu:
125
Wszystkie dostępne wersje tego obiektu:
https://www.zbc.uz.zgora.pl/publication/65820
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Wyświetl opis w formacie OAI-PMH:
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International Journal of Applied Mathematics and Computer Science (AMCS)
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| Nazwa wydania | Data |
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| Data-driven models for fault detection using kernel PCA: A water distribution system case study | 2021-10-14 |
