Using Artificial Neural Networks to Establish a Customer-cancellation Prediction Model

• Autorzy: Huang H.-C. , Chang A. Y. , Ho C.-C.

Warianty tytułu

PL

Model anulowania klientów, oparty na sztucznych sieciach neuronowych

• Języki publikacji: EN

Abstrakty

EN

In the past, judgments concerning customer cancellations relied primarily on managers’ experience. Prediction errors can cause surpluses or insufficient service capacity. Data mining technology can improve prediction and judgment accuracy. This study applies back propagation neural networks and general regression neural networks to establish a customer-cancellation prediction model. The empirical results showed that both prediction models possessed good predictive abilities and can aid in service capacity scheduling.

PL

W artykule opisano zastosowanie sieci neuronowych o propagacji wstecznej (ang. BPNN) oraz regresji generalnej (ang. GRNN) w budowie modelu anulowania klientów. Działanie to zwykle opiera się na doświadczeniu manager’a, co może doprowadzić do błędnych decyzji. Rezultaty badań empirycznych dowodzą dobrych własności przewidywania i możliwej użyteczności w określaniu potencjalnych działań z klientem opracowanych modeli.

Słowa kluczowe

EN

back-propagation neural network; general regression neural networks; receiver operating characteristic

PL

BPNN; GRNN; charakterystyka odbioru

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2013
• Tom: R. 89, nr 1b
• Strony: 178--180
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wykr.

Twórcy

autor

Huang H.-C.

• Yu Da University

autor

Chang A. Y.

• Chinese Culture University

autor

Ho C.-C.

• Chinese Culture University

Bibliografia

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