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), 2015. Published by Science Publishing Group |
Bankrupcy firms, Classification problems, Fuzzy logic, Linear programming, Ranking function
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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
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
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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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}
}
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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