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Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms
American Journal of Applied Mathematics
Volume 3, Issue 2, April 2015, Pages: 75-80
Received: Feb. 15, 2015; Accepted: Feb. 25, 2015; Published: Apr. 2, 2015
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Slah Benyoussef, Airport Rd, Al-Imam Muhammad Ibn Saud Islamic University, Riyadh 11432, Arabie Saoudite; Faculté des Sciences Economiques et de Gestion de Sfax, route Aéroport km 4, BPN°1088, 3018 Sfax, Tunisie
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In many real applications, the data of classification problems cannot be precisely measured. However, in an increasingly complex environment, these variables can be imprecise, qualitative or linguistic. In such a case, fuzzy set theory seems to be the convenient tool to fill this insufficiency. Thus, we proposed a new approach, based on the ranking function, which consists in solving the classification problems via fuzzy linear programming model. This approach has been applied for the financial distress firms. The obtained results are satisfactory in terms of correctly classified rates
Bankrupcy firms, Classification problems, Fuzzy logic, Linear programming, Ranking function
To cite this article
Slah Benyoussef, Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms, American Journal of Applied Mathematics. Vol. 3, No. 2, 2015, pp. 75-80. doi: 10.11648/j.ajam.20150302.17
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