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Reseach Article

Similarity Measures of Tangent, Cotangent and Cosines in Neutrosophic Environment and their Application in Selection of Academic Programs

by Muhammad Naveed Jafar, Asma Farooq, Komal Javed, Nazia Nawaz
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 46
Year of Publication: 2020
Authors: Muhammad Naveed Jafar, Asma Farooq, Komal Javed, Nazia Nawaz
10.5120/ijca2020919980

Muhammad Naveed Jafar, Asma Farooq, Komal Javed, Nazia Nawaz . Similarity Measures of Tangent, Cotangent and Cosines in Neutrosophic Environment and their Application in Selection of Academic Programs. International Journal of Computer Applications. 177, 46 ( Mar 2020), 17-24. DOI=10.5120/ijca2020919980

@article{ 10.5120/ijca2020919980,
author = { Muhammad Naveed Jafar, Asma Farooq, Komal Javed, Nazia Nawaz },
title = { Similarity Measures of Tangent, Cotangent and Cosines in Neutrosophic Environment and their Application in Selection of Academic Programs },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2020 },
volume = { 177 },
number = { 46 },
month = { Mar },
year = { 2020 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number46/31217-2020919980/ },
doi = { 10.5120/ijca2020919980 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:48:47.652999+05:30
%A Muhammad Naveed Jafar
%A Asma Farooq
%A Komal Javed
%A Nazia Nawaz
%T Similarity Measures of Tangent, Cotangent and Cosines in Neutrosophic Environment and their Application in Selection of Academic Programs
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 46
%P 17-24
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Similarity measures have wide range of applications in real-world such as patterns, face recognitions, codding etc. In this paper it is intended to determine the tangent, cosine and cotangent similarity measure for single valued Neutrosophic sets and will compare the accuracy of all above similarity measures and applied it in decision making problems such as selection of an academic programs.

References
  1. Ansari.Q.A, Biswas.R and Aggarwal.S, (2011).Proposal for applicability of neutrosophic set theory medical AI, International Journal of computer Applications,27(5):5-11
  2. Atanassov.K, (1986).Intuitionistic fuzzy sets, Fuzzy sets and systems, 20:87-96.
  3. Atanassov.K, Gargov.G, (1989). Interval valued Intuitionistic fuzzy sets, Fuzzy sets and system, 31:343-349.
  4. Biswas.P, Pramanik.S, and Giri.C.B, (2015). Cosine similarity measure based multi-attribute decision making with trapezoidal fuzzy neutrosophic numbers, Neutrosophic Sets and System, 8: 47-58.
  5. Broumi.S, and, Smarandache.F, (2013). Several similarity measures of neutrosophic sets, Neutrosophic Sets and Systems 1: 54-62.
  6. Broumi.S, and Smarandache.F, (2013). Correlation coefficient of interval neutrosophic set, Periodical of Applied Mechanics and Materials, with the title Engineering Decisions and Scientific Research in Aerospace, Robotics, Biomechanics, Mechanical Engineering and Manufacturing, Proceedings of the International Conference ICMERA, Bu- charest, 436.
  7. Broumi.S and Samarandache.F, (2014).Cosine similarity measure of interval valued neutrosophic set,Neutrosophic sets and systems,5:15-20.
  8. Cheng.D.H and Guo.Y, (2008).A new neutrosophic approach to image thresholding, New mathematics and Natural computation, 4(3):291-308
  9. Chen.M.S,Yeh.M.S and Hsiao.H.P, (1995).A comparison of Similarity measure of fuzzy value, fuzzy sets and system,72:79-89.
  10. Chen.M.S, (1998).A new approach to handling fuzzy decision making problems, IEEE Transactions on systems man and Cybemetics, 8: 1012-1016.
  11. Guo.Y and Cheng.D.H,(2009).New neutrosophic approach to image segmentation, Pattern recognition, 42: 587-595.
  12. Hyung.K.L, Song.S.Y and Lee.M.K, (1994).Similarity measure between fuzzy sets and between elements, Fuzzy sets and systems, 62:291-293.
  13. Jafar.N.M, Saqlain.M, Saeed.M, Abbas.Q (2020), Application of Soft-Set Relations and Soft Matrices in Medical Diagnosis using Sanchez’s Approach , International Journal of Computer Applications, 177(32): 7-11.
  14. Jafar.N.M, Muniba.K, Saeed.A, Abbas.S, Bibi.I (2019), Application of Sanchez’s Approach to Disease Identification Using Trapezoidal Fuzzy Numbers, International Journal of Latest Engineering Research and Applications, 4(9):51-57
  15. Jafar.N.M, Faizullah, Shabbir.S, Alvi.F.M.S, Shaheen.L (2020), Intuitionistic Fuzzy Soft Matrices, Compliments and Their Relations with Comprehensive Study of Medical Diagnosis, International Journal of Latest Engineering Research and Applications, 5(1): 23-30.
  16. Jafar.N.M, Saeed.A, Waheed.M, Shafiq.A (2020), A Comprehensive Study of Intuitionistic Fuzzy Soft Matrices and its Applications in Selection of Laptop by Using Score Function, International Journal of Computer Applications, 177(38): 8-17.
  17. Jafar.N.M, Khan.R.M, , Sultan.H, Ahmad.N (2020), Interval Valued Fuzzy Soft Sets and Algorithm of IVFSS Applied to the Risk Analysis of Prostate Cancer, International Journal of Computer Applications, 177(38): 18-26.
  18. Jafar.N.M, Imran.R, Hassan.S, Riffat.A, Shuaib.R (2020), Medical Diagnosis Using Neutrosophic Soft Matrices and Their Compliments, International Journal of Advanced Research in Computer Science, 11(1):1-3
  19. Kharal.A, (2013). A neutrosophic multi-criteria decision making method, New Mathematics and natural computation Creighton University USA.
  20. Majumder,P and Samanta.K.S, (2014). On similarity and entropy of neutrosophic sets, Journal of Intelligent and Fuzzy Systems 26:1245–1252
  21. Mondal.K and Pramanik.S, (2014).Multi-criteria group decision making approach for teacher recruitment in higher education under simplified neutrosophic environment, Neutrosophic sets and system, 6:28-34.
  22. Mondal .K and Pramanik.S, (2015).Neutrosophic decision making model of school choice, Neutrosophic sets and systems, 7:62-68.
  23. Mondal.K and Paramanik.S, (2014).A study on problems of Hijras in west Bengal based on neutrosophic cognitive maps, Neutrospohic sets and system, 5:21-26.
  24. Mondal.K and Pramanik.S, (2015).Intuitimistic fuzzy similarity measure based on tangent function and its application to multi attribute decision, Global Journal of Advanced Research,2(2):404-471.
  25. Pappis.C.P and Karacapilidis .I.N, (1993).A comparative assessment of measure of similarity of fuzzy values, Fuzzy sets and system, 56:171-174
  26. Pramanik.S and Chackrabarti.N.S,(2013).A study on problems of construction workers in west Bengal based on neutrosophic cognitive maps, International Journal of innovative Research in science, engineering and technology,2(11),6387-6394.
  27. Pramanik.S, Roy.K.T, (2014).Neutrosophcic game theoretic approach to Indo-Pak conflict over Jammu-Kashmir, neutrosophic sets and systems, 2:82-101.
  28. Riaz.M, Saeed.M, Saqlain.M, Jafar.N (2019), Impact of Water Hardness in Instinctive Laundry System Based on Fuzzy Logic Controller, Punjab University Journal of Mathematics, 51(4):73-84
  29. Saeed, M., Zulqarnain, M. and Dayan, F. (2018). TOPSIS analysis for the prediction of diabetes based on general characteristics of humans. Int. J. of Pharm. Sci. and Research. 9: 2932-2939
  30. Saqlain.M.Jafar.N, Riffat.A (2018), Smart Phone Selection by Consumers’ In Pakistan: FMCGDM Fuzzy Multiple Criteria Group Decision Making Approach, Gomal University Journal of Research, 34 (1): 27-31.
  31. Saqlain.M, Jafar.N, Hamid.R,Shahzad.A. (2019), Prediction of Cricket World Cup 2019 by TOPSIS Technique of MCDM-A Mathematical Analysis, International Journal of Scientific & Engineering Research, 10(2): 789-792
  32. Saqlain.M, Naz.K, Ghaffar.K, Jafar.N.M (2019), Fuzzy Logic Controller: The Impact of Water pH on Detergents, Scientific Inquiry of Review 3(3):16–29
  33. Saqlain M, Saeed M, Ahmad M. R, Smarandache F, (2019), Generalization of TOPSIS for Neutrosophic Hypersoft set using Accuracy Function and its Application, Neutrosophic Sets and Systems (NSS), 27: 131-137.
  34. Smarandache.F, (1998). A unifying field in logics, neutrosophy: neutrosophic probability set and logic, Rehoboth American Res.press: 1-141
  35. Smarandache.F,(1999).Linguistic paradoxes and tautologies, Libertas Mathematica,Universityof Texas at Arlington IX :143-154.
  36. Szmidt.E and Kacprzyk.J, (2004).Medical diagnostic reasoning using a similarity measure for intuitionistic fuzzy sets, Notes on intuitionistic fuzzy sets,10(4):61-69.
  37. Tian.MY, (3012).A new fuzzy similarity based on cotangent function for medical diagnosis, Adv. Model option, 5(2):151-156.
  38. Wang.H, Smarandache.F, Zhang.Y and Sunderraman.R, (2010).Single valued Neutrosophic sets, Multi space and Multistructure, 4:410-413.
  39. Wang.J.W,(1997).New similarity measure on fuzzy sets and element, fuzzy sets and system,85:305-309.
  40. Ye.J,(2013).Multicriteria decision making method using the correlation coefficient using single valued neutrosophic environment, International Journal of general system,42(4):386-394.
  41. Ye.J, and Zhang.Q,(2012). Single valued neutrosophic similarity measures for multiple attribute decision making Neutrosophic Sets and System 2: 48-54.
  42. Ye.J, (2014).Similarity measures between interval neutrosophic sets and their multi criteria decision making method, Journal of Intelligent and Fuzzy Systems 26:165-172.
  43. Ye.J, (2014).Vectors similarity measure of simplified neutrosophic sets and their application in multi criteria decision making, International Journal of fuzzy systems, 16(2):204-215
  44. Ye.J, (2014) Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses, Artificial Intelligence in Medicine doi: 10.1016/j.artmed.2014.12.007.
  45. Ye.S and Ye.J ,(2014).Dice similarity measure between single valued neutrosophic multi sets and its application in medical diagnosis , Neurosophic sets and systems,6:49-54.
  46. Ye.S,Fu.J and Ye.J ,(2014).Medical diagnosis sing distance based similarity measures for single valued neutrosophic multi sets, Neutrosophic sets and system,7:47-52.
  47. Ye.J,(2015).Single valued neutrosophic similarity measures based on cotangent function and their application in the fault diagnosis of steam turbine,Soft comput,DOI 10.1007/s00500-015-1818-y.
  48. Zadeh.A.L, (1965).Fuzzy sets, Information and control, 8:338-353.
  49. Zadeh.A.L, (1975).The concept of linguistic variable and its application to approximate reasoning I , Inform sci, 8:199-249.
  50. Zhang.M,Zhang.L and Cheng.D.H,(2010).A neutrosophic approach to image segmentation based on watershed method, single processing,90(5):1510-1517.
Index Terms

Computer Science
Information Sciences

Keywords

Similarity Measures Neutrosophic Sets Tangent Measures Cosine Measures Cotangent Measures