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2010, vol. 57, br. 1, str. 43-60
Insurability challenges under uncertainty: An attempt to use the artificial neural network for the prediction of losses from natural disasters
(naslov ne postoji na srpskom)
aResearch Unit in Development Economy, Faculty of Economics Sciences and Management, University of Sfax, Tunisia
bHigher School of Commerce, University of Sfax, Tunisia

e-adresarim_jemli@yahoo.fr, nouri.chtourou@fseg.rnu.tn, Rochdi.Feki@escs.rnu.tn
Ključne reči: natural disaster losses; insurability; uncertainty; multilayer perceptron neural network; prediction
(ne postoji na srpskom)
The main difficulty for natural disaster insurance derives from the uncertainty of an event's damages. Insurers cannot precisely appreciate the weight of natural hazards because of risk dependences. Insurability under uncertainty first requires an accurate assessment of entire damages. Insured and insurers both win when premiums calculate risk properly. In such cases, coverage will be available and affordable. Using the artificial neural network - a technique rooted in artificial intelligence - insurers can predict annual natural disaster losses. There are many types of artificial neural network models. In this paper we use the multilayer perceptron neural network, the most accommodated to the prediction task. In fact, if we provide the natural disaster explanatory variables to the developed neural network, it calculates perfectly the potential annual losses for the studied country.
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O članku

jezik rada: engleski
vrsta rada: izvorni naučni članak
DOI: 10.2298/PAN1001043J
objavljen u SCIndeksu: 07.04.2010.