Neural networks approach for determining total claim amounts in insurance
Yükleniyor...
Tarih
2009
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science Bv
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, we present an approach based on neural networks, as an alternative to the ordinary least squares method, to describe the relation between the dependent and independent variables. It has been suggested to construct a model to describe the relation between dependent and independent variables as an alternative to the ordinary least squares method. A new model, which contains the month and number of payments, is proposed based on real data to determine total claim amounts in insurance as an alternative to the model suggested by Rousseeuw et al. (1984) [Rousseeuw, P., Daniels, B., Leroy, A., 1984. Applying robust regression to insurance. Insurance: Math. Econom. 3,67-72] in view of an insurer. (C) 2009 Elsevier B.V. All rights reserved.
Açıklama
Tank, Fatih/0000-0003-3758-396X
Anahtar Kelimeler
Neural networks, Least squares method, Total claim amount, Claim amount payments, Fuzzy if-then rules
Kaynak
Insurance Mathematics & Economics
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
45
Sayı
2
Künye
closedAccess
