Fuzzy soft attribute correlation coefficient and application to data of human trafficking.

  • Santanu Acharjee Debraj Roy College.
  • Diganta Jyoti Sarma Central Institute of Technology.
  • Robert A. Hanneman University of California.
  • John N. Mordeson Creighton University.
  • Davender S. Malik Creighton University.

Resumen

In this paper, we introduce fuzzy soft attribute correlation coefficient and apply it to find the correlation between vulnerability government response of various countries related to human trafficking based on six regions with the help of data from “The Global Slavery Index 2016”. Comparison of fuzzy soft attribute correlation coefficients is done with the conventional analysis of sociology by calculating Pearson’s zero-order product-moment correlations. Along with these, some fundamental concepts of mathematical statistics are developed with respect to fuzzy soft set.

Biografía del autor

Santanu Acharjee, Debraj Roy College.
Economics and Computational Rationality Group, Department of Mathematics.
Diganta Jyoti Sarma, Central Institute of Technology.
Department of Mathematics, BTAD.
Robert A. Hanneman, University of California.
Department of Sociology.
John N. Mordeson, Creighton University.
Center for Mathematics of Uncertainty, Department of Mathematics.
Davender S. Malik, Creighton University.
Center for Mathematics of Uncertainty, Department of Mathematics.

Citas

S. Acharjee and J. N. Mordeson , Soft statistics with respect to utility and application to human trafficking, New Math. Nat. Comput. 13(03), pp. 289-310, (2017).

N. Çağman, S. Karataş and S. Enginoglu, Soft topology, Comput. Math. Appl., 62, pp. 351-358, (2011).

D. Chen, The parametrization reduction of soft sets and its application, Comput. Math. Appl. , 49, pp. 757-763, (2005).

http://www.globalslaveryindex.org/, The Global Slavery index, (2016).

https://www.unodc.org/unodc/en/human-trafficking/what-is-human-trafficking.html, United Nations Office on Drug and Crime.

Y. Leung, A fuzzy set analysis of sociometric structure, Jour. Math. Socio. 7, pp. 159-180, (1980).

H. Li and Y. Shen, Similarity measures of fuzzy soft sets based on different distances, Fifth Int. Symp. Comput. Intel. and Design, pp. 527- 529, (2012).

S. Li, Measuring the fuzziness of human thoughts: an application of fuzzy sets to sociological research, Jour. Math. Socio. 14(1), pp. 67-84, (1989).

P. K. Maji, R. Biswas and A. R. Roy , Fuzzy soft sets, Jour. Fuzzy Math. 9(3), pp. 589-602, (2001).

P. K. Maji, R. Biswas and A. R. Roy, Soft set theory, Comput. Math. Appl. 45, pp. 555-562, (2003).

P. Majumdar and S. K. Samanta , On similarity measures of fuzzy soft sets, Int. Jour. Adv. Soft. Comput. Appl. 3(2), 8 pages, (2011).

D.Molodtsov, Soft set theory-first results, Comput. Math. Appl. 37, pp. 19-31,(1999).

J. N. Mordeson, M. Mallenby, S. Mathew and S. Acharjee, Human trafficking: Policy intervention, New Math. Nat. Comput. 13(03), pp. 341-358, (2017).

D. Pei and D. Miao, From soft sets to information systems, Proceedings of the IEEE international conference on granular computing, 2, pp. 617-621, (2005).

Trafficking in Persons: Global Patterns, United Nations Office on Drugs and Crime, Trafficking in Persons Citation Index.

Z. Xiao and Y. Zou, A comparative study of soft sets with fuzzy sets and rough sets, Jour. Intel. Fuzzy Syst. 27, pp. 425-434, (2014).

L. A. Zadeh, Fuzzy sets, Inform. Control. 8(3), pp. 338-353, (1965).

Publicado
2018-11-22
Cómo citar
Acharjee, S., Sarma, D., Hanneman, R., Mordeson, J., & Malik, D. (2018). Fuzzy soft attribute correlation coefficient and application to data of human trafficking. Proyecciones. Revista De Matemática, 37(4), 637-681. Recuperado a partir de http://www.revistaproyecciones.cl/article/view/3273
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