Variable precision rough set for group decision-making: an application

• Autores: Gang Xie, J. Zhang, K.K. Lai, L. Yu
• Localización: International journal of approximate reasoning, ISSN 0888-613X, Vol. 49, Nº 2, 2008, págs. 331-343
• Idioma: inglés
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• Resumen

  • This study uses the variable precision rough set (VPRS) model as a tool to support group decision-making (GDM) in credit risk management. We consider the case that the classification in decision tables consisting of risk exposure (RE) may be partially erroneous, and use a variable precision factor ßk to adjust the classification error. In this paper, we firstly combine VPRS and AHP to obtain the weight of condition attribute sets decided by each decision-maker (DM). Then, the integrated risk exposure (IRE) of attributes is obtained based on the three VPRS-based models. Subsequently, a new procedure of obtaining ßk-stable intervals for DMk is investigated. To verify the effectiveness of these proposed methods, an illustrative example is presented. The experimental results suggest that the VPRS-based IRE have advantages in recognizing important attributes.