Topological Method for a Study of Discriminating Three Categories of Banks and its use in Attributes Reduction

Authors

  • M. A. El Safty   Department of Mathematics and Statistics, Faculty of Science, Taif University, KSA, Saudi Arabia

DOI:

https://doi.org/10.32628/IJSRSET207541

Keywords:

Knowledge discovery, Rough set, Positive region, Decision making, Types banking.

Abstract

This work approaches the problem of knowledge extraction within the banking domain using rough set, rough set theory can be considered as a topological method. Our main goal is to separate of the accounting attributes to discriminate between Islamic, mixed, and conventional banks. To this end, we have used the positive region in the rough set framework is traditional uncertainty measurements, used usually as in attribute reduction. Attributes banks will be separated and we are classified with a given decision, then we theoretically analyze the variance of the rough set. In the actual application, we used the financial semantics based on the domain expertise of experts to determine between the competing approaches. The results show the value of shared financial information for distinguishing between the three types of banks with certain attributes. These results are helping us offer a new view of attribute reduction in knowledge. We used MATLAB for our applications in computing.

References

  1. Beck, T.; Demirgüç-Kunt, A.; Merrouche, O. (2013) Islamic vs. conventional banking: Business model, efficiency and stability. Journal of Banking and Finance. 37, 433–447.
  2. https://doi.org/10.1016/j.jbankfin.2012.09.016
  3. Ben Ishak Anis; Feki Asma. (2016) A discriminating study between three categories of banks based on statistical learning approaches. Intelligent Data Analysis. 20, 1199-1221. https://doi.org/10.3233/ida-160863
  4. Ben Othman, H.; Mersni, H. (2014) The use of discretionary loan loss provisions by Islamic banks and conventional banks in the Middle East region: A comparative study. Studies in Economics and Finance. 31, 106–128.
  5. Dar, H. A.; Presely, R.J. (2000) Lack of profit loss sharing in Islamic banking: Management and control imbalances, Economic research paper N? 00/24, Department of Economics, Southborough University. 2000.
  6. Elsafty, M. A.; Alkhathami, A. M. (2019) A Topological method for reduction of digital information uncertainty. Soft Computing. 190, 1344–1352. https://doi.org/10.1007/s00500-019-03920-9
  7. Elsafty, M. A.; Mohamed, E. H. (2018) Attribute priority arrangement of cancellations in the life insurance using rough set. Int. J. Cust Relationship Market Manag (IJCRMM). 9, 16–43. https://doi.org/10.4018/IJCRMM.2018100102
  8. Johnes, J.; Izzeldin, M.; Pappas, V. (2014) A comparison of performance of Islamic and conventional banks 2004–2009. Journal of Economic Behavior and Organization. 103: 93–107.
  9. Kang, X.; Li, D.; Wang, S.; Qu, K. (2013) Rough set model based on formal concept analysis. Information Sciences. 222, 611–625. https://doi.org/10.1016/j.ins.2012.07.052
  10. Lashin, E. F.; Kozae, A. M.; Abo Khadra, A. A.; Medhat, T. (2005) Rough set theory for topological space. International Journal of Approximate Reasoning. 40, 35-43. http://dx.doi.org/10.1016/j.ijar.2004.11.007
  11. Li, J.; Mei, CH.; Lv, Yu. (2012) Knowledge reduction in real decision formal contexts. Information Sciences. 189, 191-207. https://doi.org/10.1016/j.ins.2011.11.041
  12. Liang, J. Y.; Wang, F.; Dang, C. Y.; Qian, Y. (2014) H. A Group Incremental Approach to Feature Selection Applying Rough Set Technique. IEEE Transactions on Knowledge and Data Engineering. 26, 294-308.
  13. Olson, D.; Zoubi, T. A. (2008) Using accounting ratios to distinguish between Islamic and conventional banks in the GCC region. The International Journal of Accounting. 43, 45–65.
  14. Pawlak, Z. (1982) Rough sets. Int. J. Inf. Computer Sci. 11, 341-356.
  15. Pawlak, Z. (1991) Rough sets. Theatrical Aspects of Reasoning about Data. 9, 1-237. https://doi.10.1007/978-94-011-3534-4_7
  16. Turen, S. (1996) Performance and risk analysis of the Islamic banks: The case of Bahrain Islamic bank. Journal of King Abdulaziz University: Islamic Economics. 8, 3–14.
  17. Yao, Y. Zhao, Y. Attribute reduction in decision-theoretic rough set models. Information Sciences. 2008, 178, 3356-3373. https://doi.org/10.1016/j.ins.2008.05.010
  18. Zhang, W. X.; Mi, J. S.; Wu W. Z. (2003) Knowledge reduction in inconsistent information systems. Chinese J. of Computers. 1, 12-18.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2020-10-30

Issue

Volume 7, Issue 5, September-October-2020

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. A. El Safty "Topological Method for a Study of Discriminating Three Categories of Banks and its use in Attributes Reduction" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 5, pp.221-233, September-October-2020. Available at doi : https://doi.org/10.32628/IJSRSET207541