Comparative study of learning methods for artificial neural network

• Autorzy: Tiliouine H.

Warianty tytułu

PL

Badania porównawcze metod uczenia sieci neuronowej

• Języki publikacji: EN

Abstrakty

EN

The paper presents a comparative study of various learning methods for artificial neural network. The methods are: the backpropagation BP, the recursive least squares RLS, the Zangwill's method ZGW and the method based on evolutionary algorithm EA. The study consists of evaluating the learning effectiveness of these methods and selecting the most efficient one to be used in the designing of an adaptive neural voltage controller for a synchronous generator.

PL

W artykule przedstawiono wyniki badań porównawczych metod uczenia sieci neuronowych takich jak: metoda propagacji wstecznej błędów, rekurencyjna metoda najmniejszych kwadratów, metoda Zangwill'a, metoda algorytmów ewolucyjnych. Celem tych badań jest dobieranie najefektywniejszej metody uczenia do projektowania adaptacyjnego neuronowego regulatora napięcia generatora synchronicznego.

Słowa kluczowe

EN

learning methods; artificial neural network (ANN); neural voltage controller

PL

metody uczenia; sieć neuronowa; neuronowy regulator napięcia

• Wydawca: Wydawnictwo PAK
• Czasopismo: Pomiary Automatyka Kontrola
• Rocznik: 2007
• Tom: R. 53, nr 4
• Strony: 117--121
• Opis fizyczny: Bibliogr. 20 poz., rys., wykr., wzory

Twórcy

autor

Tiliouine H.

• Faculty of Electrical and Control Engineering, Gdansk University of Technology,

Bibliografia

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