1. Yan, D., K. Wu, P.A. Ejegwa, X. Xie and Y. Feng, 2023. Pythagorean fuzzy partial correlation measure and its application. Symmetry, Vol. 15. 10.3390/sym15010216.
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2. Ejegwa, P.A., S. Wen, Y. Feng, W. Zhang and J. Liu, 2023. A three-way Pythagorean fuzzy correlation coefficient approach and its applications in deciding some real-life problems. Appl. Intell., 53: 226-237.
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3. Wu, K., P.A. Ejegwa, Y. Feng, I.C. Onyeke, S.E. Johnny and S. Ahemen, 2022. Some enhanced distance measuring approaches based on pythagorean fuzzy information with applications in decision making. Symmetry, Vol. 14. 10.3390/sym14122669.
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4. Onyeke, I.C. and P.A. Ejegwa, 2022. Modified Senapati and Yager’s Fermatean Fuzzy Distance and Its Application in Students’ Course Placement in Tertiary Institution. In: Book cover Book cover Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain, Sahoo, L., T. Senapati and R.R. Yager, (Eds.), Springer Nature Singapore, pp: 237–253.
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5. Ejegwa1, P.A. and D. Zuakwagh, 2022. Fermatean fuzzy modified composite relation and its application in pattern recognition. J. Fuzzy Ext. Appl., 3: 140-151.
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6. Ejegwa, P.A., Y. Feng, S. Tang, J.M. Agbetayo and X. Dai, 2022. New Pythagorean fuzzy-based distance operators and their applications in pattern classification and disease diagnostic analysis. Neural Comput. Appl., 10.1007/s00521-022-07679-3.
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7. Ejegwa, P.A., G. Muhiuddin, E.A. Algehyne, J.M. Agbetayo and D. Al-Kadi, 2022. An enhanced fermatean fuzzy composition relation based on a maximum-average approach and its application in diagnostic analysis. J. Math., 10.1155/2022/1786221.
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8. Ejegwa, P.A., 2022. Decision-Making on Patients' Medical Status Based on a q-Rung Orthopair Fuzzy Max-Min-Max Composite Relation. In: q-Rung Orthopair Fuzzy Sets, Garg, H., (Eds.), Springer Nature Singapore, ISBN: 978-981-19-1448-5, pp: 47–66.
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9. Ejegwa, P.A. and S. Ahemen, 2022. Enhanced intuitionistic fuzzy similarity operators with applications in emergency management and pattern recognition. Granul. Comput., 10.1007/s41066-022-00334-1.
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10. Ejegwa, P.A. and J.M. Agbetayo, 2022. Similarity-Distance Decision-Making Technique and its Applications via Intuitionistic Fuzzy Pairs. J. Comput. Cognitive Eng., 10.47852/bonviewJCCE512522514.
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11. Ejegwa, P.A. and I.C. Onyeke, 2022. Some New Distance and Similarity Algorithms for Pythagorean Fuzzy Sets With Application in Decision-Making Problems. In: Handbook of Research on Advances and Applications of Fuzzy Sets and Logic, Broumi, S. (Ed.), IGI Global, Hershey, Pennsylvania, ISBN-13: 9781799879794, pp: 192-211.
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12. Ejegwa, P.A. and I.C. Onyeke, 2022. Fermatean fuzzy similarity measure algorithm and its application in students' admission process. Int. J. Fuzzy Comput. Modell., 10.1504/IJFCM.2021.10047079.
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13. Ejegwa, P.A. and B. Davvaz, 2022. An improved composite relation and its application in deciding patients medical status based on a q-rung orthopair fuzzy information. Comp. Appl. Math., Vol. 41. 10.1007/s40314-022-02005-y.
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14. Ejegwa, P.A., Y. Feng, S. Wen and W. Zhang, 2021. Determination of pattern recognition problems based on a pythagorean fuzzy correlation measure from statistical viewpoint. 2021 13th International Conference on Advanced Computational Intelligence (ICACI), May 14-16, 2021, IEEE Xplore, Tunis, Tunisia, pp: 132-139.
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15. Ejegwa, P.A., V. Adah and I.C. Onyeke, 2021. Some modified pythagorean fuzzy correlation measures with application in determining some selected decision-making problems. Granular Comput., 10.1007/s41066-021-00272-4.
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16. Ejegwa, P.A., V. Adah and I.C. Onyeke 2021. Some Modified Pythagorean Fuzzy Correlation Measures with Application in Determining some Selected Decision-Making Problems. Granul. Comput. 10.1007/s41066-021-00272-4.
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17. Ejegwa, P.A., S. Wen, Y. Feng, W. Zhang and J. Chen, 2021. Some new pythagorean fuzzy correlation techniques via statistical viewpoint with applications to decision-making problems. J. Intell. Fuzzy Syst., 10.3233/jifs-202469.
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18. Ejegwa, P.A., J.A. Awolola, J.M. Agbetayo and I.M. Adamu 2021. On the Characterisation of Anti-fuzzy Multigroups. Korea Open Access J. 21: 307-318.
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19. Ejegwa, P.A., C. Jana and M. Pal, 2021. Medical diagnostic process based on modified composite relation on pythagorean fuzzy multi-sets. Granular Comput., 10.1007/s41066-020-00248-w.
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20. Ejegwa, P.A. and Jana C. 2021. Some New Weighted Correlation Coefficients Between Pythagorean Fuzzy Sets and Their Applications. In: Some New Weighted Correlation Coefficients Between Pythagorean Fuzzy Sets and Their Applications. Ejegwa, P.A. and Jana C. Springer, Singapore 26.
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21. Ejegwa, P.A. and J.A. Awolola, 2021. Real-life decision making based on a new correlation coefficient in pythagorean fuzzy environment. Ann. Fuzzy Math. Inf., 21: 51-67.
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22. Ejegwa, P.A. and I.C. Onyeke, 2021. A novel intuitionistic fuzzy correlation algorithm and its applications in pattern recognition and student admission process. Int. J. Fuzzy Syst. Appl., Vol. 11. 10.4018/IJFSA.285984.
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23. Ejegwa, P., S. Wen, Y. Feng, W. Zhang and N. Tang, 2021. Novel Pythagorean fuzzy correlation measures via Pythagorean fuzzy deviation, variance and covariance with applications to pattern recognition and career placement. IEEE Trans. Fuzzy Syst., 10.1109/tfuzz.2021.3063794.
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24. Augustine, E.P., 2021. Novel correlation coefficient for intuitionistic fuzzy sets and its application to multi-criteria decision-making problems. Int. J. Fuzzy Syst. Appl., 10: 39-58.
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25. Agbetayo, J.M. and P.A. Ejegwa 2021. Certain Results on Metric and Norm in Fuzzy Multiset Setting. Ratio Math. 40: 67-75.
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26. Ejegwa, P.A., Y. Feng and W. Zhang, 2020. Pattern recognition based on an improved szmidt and kacprzyk’s correlation coefficient in pythagorean fuzzy environment. In: Advances in Neural Networks – ISNN 2020. ISNN 2020. Lecture Notes in Computer Science, Han, M., S. Qin and N. Zhang, Springer, Cham, Switzerland, ISBN-13 978-3-030-64220-4, pp: 190-206.
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27. Ejegwa, P.A., I.C. Onyeke and V. Adah, 2020. An algorithm for an improved intuitionistic fuzzy correlation measure with medical diagnostic application. Ann. Optim. Theory Pract., 3: 51-68.
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28. Ejegwa, P.A., I.C. Onyeke and V. Adah, 2020. A pythagorean fuzzy algorithm embedded with a new correlation measure and its application in diagnostic processes. Granular Comput., 10.1007/s41066-020-00246-y.
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29. Ejegwa, P.A., 2020. An improved correlation coefficient between intuitionistic fuzzy sets and its applications to real-life decision-making problems. Notes Intuitionistic Fuzzy Sets, 26: 1-14.
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30. Ejegwa, P.A., 2020.

    Some characterizations of fuzzy comultisets and quotient fuzzy multigroups.
    

    Ratio Math., 38: 237-259.
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31. Ejegwa, P.A. and J.M. Agbetayo, 2020. On commutators of fuzzy multigroups. Earthline J. Math. Sci., 4: 189-210.
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32. Ejegwa, P.A. and I.C. Onyeke, 2020. Medical diagnostic analysis on some selected patients based on modified Thao et al.u2019s correlation coefficient of intuitionistic fuzzy sets via an algorithmic approach. J. Fuzzy Ext. Appl., 1: 130-141.
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33. Ejegwa, P.A. and I.C. Onyeke, 2020. Intuitionistic fuzzy statistical correlation algorithm with applications to multicriteriau2010based decisionu2010making processes. Int. J. Intell. Syst., 10.1002/int.22347.
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34. Ejegwa P.A., 2020. Pythagorean fuzzy multiset and its application to course placements. Open Journal of Discrete Applied Mathematics 3: 55-74.
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35. Ejegwa P.A., 2020. New similarity measures for pythagorean fuzzy sets with applications. International Journal of Fuzzy Computation and Modelling 3: 75-75.
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36. Ejegwa P.A., 2020. Improved composite relation for pythagorean fuzzy sets and its application to medical diagnosis. Granular Computing 5: 277-286.
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37. Ejegwa P.A., 2020. Concept of anti multigroups and its properties. Earthline Journal of Mathematical Sciences 4: 83-97.
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38. Ejegwa P. A., 2020. Generalized triparametric correlation coefficient for pythagorean fuzzy sets with application to mcdm problems. Granular Computing 10.1007/s41066-020-00215-5 http://dx.doi.org/10.1007/s41066-020-00215-5.
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39. Ejegwa, P.A. and I.M. Adamu, 2019. Distances between intuitionistic fuzzy sets of second type with application to diagnostic medicine. Notes Intuitionistic Fuzzy Sets, 25: 53-70.
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40. Ejegwa P.A., 2019. Pythagorean fuzzy set and its application in career placements based on academic performance using max–min–max composition. Complex & Intelligent Systems 5: 165-175.
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41. Ejegwa P.A., 2019. Modified zhang and xu’s distance measure for pythagorean fuzzy sets and its application to pattern recognition problems. Neural Computing and Applications 10.1007/s00521-019-04554-6 http://dx.doi.org/10.1007/s00521-019-04554-6.
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42. Ejegwa P. A. and J.A. Awolola, 2019. Novel distance measures for pythagorean fuzzy sets with applications to pattern recognition problems. Granular Computing 10.1007/s41066-019-00176-4 http://dx.doi.org/10.1007/s41066-019-00176-4.
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43. Ejegwa, P.A. and B.O. Onasanya, 2019. Improved intuitionistic fuzzy composite relation and its application to medical diagnostic process. Proceeding of 24th International Conference on Intuitionistic Fuzzy Sets '2020, 2019 Prof. Marin Drinov Publishing House of BAS (Bulgarian Academy of Sciences) 43-58.
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44. Ejegwa P.A. and A.M. Ibrahim, 2019. Some group's analogous results in multigroup setting. ANNALS OF FUZZY MATHEMATICS AND INFORMATICS 17: 231-245.
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45. Ejegwa, P.A., 2018. On normal fuzzy submultigroups of a fuzzy multigroup. Theory Applic. Math. Comput. Sci., 8: 64-80.
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46. Ejegwa, P.A., 2018. On fuzzy multigroups and fuzzy submultigroups. J. Fuzzy Math., 26: 641-654.
47. Ejegwa, P.A., 2018. On abelian fuzzy multigroups. J. Fuzzy Math., 26: 655-668.
48. Ejegwa, P.A., 2018. Homomorphism of fuzzy multigroups and some of its properties. Applic. Applied Math., 13: 114-129.
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49. Ejegwa, P.A., 2018. Distance and similarity measures for Pythagorean fuzzy sets. Granular Comput., (In Press). 10.1007/s41066-018-00149-z.
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50. Ejegwa, P.A. and A.M. Ibrahim, 2018. Homomorphism of cuts of multigroups. Gulf J. Math., 6: 61-73.
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51. Ibrahim, A.M. and P.A. Ejegwa, 2017. Multigroup actions on multiset. Ann. Fuzzy Math. Inform., 14: 515-526.
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52. Ibrahim, A.M. and P.A. Ejegwa, 2017. Characteristic submultigroups of a multigroup. Gulf J. Math., 5: 1-8.
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53. Ejegwa, P.A., 2017. Upper and lower cuts of multigroups. Prajna Int. J. Math. Sci. Applic., 1: 19-26.
54. Ejegwa, P.A. and A.M. Ibrahim, 2017. Some homomorphic properties of multigroups. Buletinul Academiei De Stiinte A Republicii Moldova. Matematica, 83: 67-76.
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55. Ejegwa, P.A. and A.M. Ibrahim, 2017. On comultisets and factor multigroups. Theory Applic. Math. Comput. Sci., 7: 124-140.
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56. Ejegwa, P.A. and A.M. Ibrahim, 2017. Normal submultigroups and comultisets of a multigroup. Quasigroups Relat. Syst., 25: 231-244.
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57. Ejegwa, P.A. and A.M. Ibrahim, 2017. Direct product of multigroups and its generalization. Int. J. Math. Combinatorics, 4: 1-18.
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58. Awolola, J.A. and P.A. Ejegwa, 2017. On some algebraic properties of order of an element of a multigroup. Quasigroups Relat. Syst., 25: 21-26.
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59. Ibrahim, A.M. and P.A. Ejegwa, 2016. A survey on the concept of multigroups. J. Niger. Assoc. Math. Phys., 38: 1-8.
60. Ejegwa, P.A., L.N. Kwarkar and K.N. Ihuoma, 2016. Application of intuitionistic fuzzy multisets in appointment process. Int. J. Comput. Applic., 135: 1-4.
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61. Ejegwa, P.A., G.U. Tyoakaa and A.M. Ayenge, 2016. Application of intuitionistic fuzzy sets in electoral system. Int. J. Fuzzy Math. Archive, 10: 35-41.
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62. Ejegwa, P.A., B.B. Tyongi, S.C. Osuwa and A.A. Atime, 2016. Career determination using intuitionistic fuzzy multisets approach. MAYFEB J. Math., 1: 1-10.
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63. Ejegwa, P.A., 2016. Some operations on intuitionistic fuzzy multisets. J. Fuzzy Math., 24: 761-768.
64. Ejegwa, P.A., 2016. On intuitionistic fuzzy multisets theory and its application in diagnostic medicine. MAYFEB J. Math., 4: 13-22.
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65. Ejegwa, P.A., 2015. New operations on intuitionistic fuzzy multisets. J. Math. Inform., 3: 17-23.
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66. Ejegwa, P.A., 2015. Mathematical techniques to transform intuitionistic fuzzy multisets to fuzzy sets. J. Inform. Comput. Sci., 10: 169-172.
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67. Ejegwa, P.A., 2015. Intuitionistic fuzzy sets approach in appointment of positions in an organization via max-min-max rule. Global J. Sci. Front. Res. F: Math. Decis. Sci., 15: 1-5.
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68. Ejegwa, P.A., 2015. Intuitionistic Fuzzy Sets Theory in Decision Making. LAMBERT Academic Publishing, Germany, ISBN-13: 978-3659661785, Pages: 56.
69. Ejegwa, P.A. and J.M. Agbetayo, 2015. Norm and metric defined over fuzzy sets. Ann. Pure Applied Math., 10: 59-64.
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70. Ejegwa, P.A. and E.S. Modom, 2015. Diagnosis of viral hepatitis using new distance measure of intuitionistic fuzzy sets. Int. J. Fuzzy Math. Archive, 8: 1-7.
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71. Ejegwa, P.A., S.O. Akowe, P.M. Otene and J.M. Ikyule, 2014. An overview on intuitionistic fuzzy sets. Int. J. Scient. Technol. Res., 3: 142-145.
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72. Ejegwa, P.A., S.N. Chukwukelu and D.E. Odoh, 2014. Test of accuracy of some distance measures use in the application of intuitionistic fuzzy sets in medical diagnosis. J. Global Res. Math. Arch., 2: 55-60.
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73. Ejegwa, P.A., J.T. Alabaa and S. Yakubu, 2014. Two new algebraic properties defined over intuitionistic fuzzy sets. Int. J. Fuzzy Math. Archive, 5: 75-78.
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74. Ejegwa, P.A., B.S. Uleh and E. Onwe, 2014. Intuitionistic fuzzy sets in electoral system. Int. J. Sci. Technol., 3: 241-243.
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75. Ejegwa, P.A., A.M. Onoja and S.N. Chukwukelu, 2014. Application of intuitionistic fuzzy sets in research questionnaire. J. Global Res. Math. Arch., 2: 51-54.
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76. Ejegwa, P.A., A.M. Onoja and I.T. Emmanuel, 2014. A note on some models of intuitionistic fuzzy sets in real life situations. J. Global Res. Math. Arch., 2: 42-50.
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77. Ejegwa, P.A., A.J. Akubo and O.M. Joshua, 2014. Intuitionistic fuzzy sets in career determination. J. Inform. Comput. Sci., 9: 285-288.
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78. Ejegwa, P.A., A.J. Akubo and O.M. Joshua, 2014. Intuitionistic fuzzy set and its application in career determination via normalized Euclidean distance method. Eur. Scient. J., 10: 529-536.
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79. Ejegwa, P.A., 2014. Correspondence between fuzzy multisets and sequences. Global J. Sci. Front. Res. F: Math. Decis. Sci., 14: 51-56.
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80. Ejegwa, P.A. and O.P. Edibo, 2014. Some distance measures between Intuitionistic Fuzzy Multisets (IFMSs). Int. J. Scient. Technol. Res., 3: 332-334.
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81. Ejegwa, P.A. and J.T. Alabaa, 2014. On the correspondence between intuitionistic fuzzy sets and democracy. Int. J. Fuzzy Math. Archive, 5: 71-73.
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82. Ejegwa, P.A. and J.A. Awolola, 2014. Intuitionistic Fuzzy Multiset (IFMS) in binomial distributions. Int. J. Scient. Technol. Res., 3: 335-337.
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83. Ibrahim, A.M. and P.A. Ejegwa, 2013. Some modal operators on intuitionistic fuzzy multisets. Int. J. Scient. Eng. Res., 4: 1814-1821.
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84. Ibrahim, A.M. and P.A. Ejegwa, 2013. Remark on some operations of intuitionistic fuzzy sets. Int. J. Sci. Technol., 2: 94-96.
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85. Ejegwa, P.A. and J.A. Awolola, 2013. Some algebraic structures of Intuitionistic Fuzzy Multisets (IFMSs). Int. J. Sci. Technol., 2: 373-376.
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