Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms

Slah Benyoussef

doi:doi:10.11648/j.ajam.20150302.17

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Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms

Slah Benyoussef

Published in American Journal of Applied Mathematics (Volume 3, Issue 2)

Received: 15 February 2015 Accepted: 25 February 2015 Published: 2 April 2015

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Abstract

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

Published in	American Journal of Applied Mathematics (Volume 3, Issue 2)
DOI	10.11648/j.ajam.20150302.17
Page(s)	75-80
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Bankrupcy firms, Classification problems, Fuzzy logic, Linear programming, Ranking function

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Slah Benyoussef. (2015). Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. American Journal of Applied Mathematics, 3(2), 75-80. https://doi.org/10.11648/j.ajam.20150302.17

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ACS Style

Slah Benyoussef. Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. Am. J. Appl. Math. 2015, 3(2), 75-80. doi: 10.11648/j.ajam.20150302.17

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AMA Style

Slah Benyoussef. Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. Am J Appl Math. 2015;3(2):75-80. doi: 10.11648/j.ajam.20150302.17

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@article{10.11648/j.ajam.20150302.17,
  author = {Slah Benyoussef},
  title = {Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms},
  journal = {American Journal of Applied Mathematics},
  volume = {3},
  number = {2},
  pages = {75-80},
  doi = {10.11648/j.ajam.20150302.17},
  url = {https://doi.org/10.11648/j.ajam.20150302.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20150302.17},
  abstract = {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},
 year = {2015}
}

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TY  - JOUR
T1  - Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms
AU  - Slah Benyoussef
Y1  - 2015/04/02
PY  - 2015
N1  - https://doi.org/10.11648/j.ajam.20150302.17
DO  - 10.11648/j.ajam.20150302.17
T2  - American Journal of Applied Mathematics
JF  - American Journal of Applied Mathematics
JO  - American Journal of Applied Mathematics
SP  - 75
EP  - 80
PB  - Science Publishing Group
SN  - 2330-006X
UR  - https://doi.org/10.11648/j.ajam.20150302.17
AB  - 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
VL  - 3
IS  - 2
ER  -

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Author Information

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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APA Style

Slah Benyoussef. (2015). Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. American Journal of Applied Mathematics, 3(2), 75-80. https://doi.org/10.11648/j.ajam.20150302.17

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ACS Style

Slah Benyoussef. Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. Am. J. Appl. Math. 2015, 3(2), 75-80. doi: 10.11648/j.ajam.20150302.17

Copy | Download

AMA Style

Slah Benyoussef. Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms. Am J Appl Math. 2015;3(2):75-80. doi: 10.11648/j.ajam.20150302.17

Copy | Download

@article{10.11648/j.ajam.20150302.17,
  author = {Slah Benyoussef},
  title = {Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms},
  journal = {American Journal of Applied Mathematics},
  volume = {3},
  number = {2},
  pages = {75-80},
  doi = {10.11648/j.ajam.20150302.17},
  url = {https://doi.org/10.11648/j.ajam.20150302.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20150302.17},
  abstract = {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},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms
AU  - Slah Benyoussef
Y1  - 2015/04/02
PY  - 2015
N1  - https://doi.org/10.11648/j.ajam.20150302.17
DO  - 10.11648/j.ajam.20150302.17
T2  - American Journal of Applied Mathematics
JF  - American Journal of Applied Mathematics
JO  - American Journal of Applied Mathematics
SP  - 75
EP  - 80
PB  - Science Publishing Group
SN  - 2330-006X
UR  - https://doi.org/10.11648/j.ajam.20150302.17
AB  - 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
VL  - 3
IS  - 2
ER  -

Copy | Download