| Yazarlar |
Türkan Erbay Dalkılıç
Karadeniz Teknik Üniversitesi, Türkiye |
|
Fatih Tank
Ankara Üniversitesi, Türkiye |
Kamile ŞANLI KULA
Ahi Evran Üniversitesi, Türkiye |
| 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. |
| Anahtar Kelimeler |
| Neural networks | Least squares method | Total claim amount | Claim amount payments | Fuzzy if-then rules |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale |
| Dergi Adı | INSURANCE MATHEMATICS & ECONOMICS |
| Dergi ISSN | 0167-6687 |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Makale Dili | İngilizce |
| Basım Tarihi | 10-2009 |
| Cilt No | 45 |
| Sayı | 2 |
| Sayfalar | 236 / 241 |
| Doi Numarası | 10.1016/j.insmatheco.2009.06.004 |
| Atıf Sayıları | |
| WoS | 7 |
