• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 38, Pages: 3168-3176

Original Article

New Pythagorean Fuzzification Based on Survey Responses to Rank Learning Approach

Received Date:22 June 2023, Accepted Date:01 September 2023, Published Date:09 October 2023


Objectives: Students’ progress is determined by their learning style. The goal of this research is to use survey data to develop a new framework for the Pythagorean fuzzy number in order to establish the best learning strategy. Methods: An inventive method for translating the questionnaire’s crisp results to Pythagorean Fuzzy numbers. A new MATLAB algorithm for converting Crisp data to Pythagorean Fuzzy data was also created. The Pythagorean Fuzzy WSM is used to determine the most effective learning approach. It is also opposed with the Intuitionistic Fuzzy WSM approach. Findings: The procedure for evaluating and prioritizing strategies, as well as selecting the most efficient method. PFWSM received a score of 0.84254. According to the findings of this study, the most effective technique is activity-based learning. Except for two learning techniques, the rank determined in PFWSM will vary in all comparisons IFWSM (S), IFWSM (ES) to the rank of score. Novelty: This research presents a novel way for assessing survey questionnaire data on a Pythagorean fuzzy background. A new MATLAB algorithm for computing Pythagorean fuzzy numbers obtained from survey replies and PFWSM Ranking. This novel approach for converting survey responses to Pythagorean fuzzy type can be applied to any sort of survey.

Keywords: Pythagorean Fuzzy; Ranking; Respondent; MATLAB; WSM; Learning approach; Fuzzification


  1. Troussas C, Giannakas F, Sgouropoulou C, Voyiatzis I. Collaborative activities recommendation based on students’ collaborative learning styles using ANN and WSM. Interactive Learning Environments. 2023;31(1):54–67. Available from: https://doi.org/10.1080/10494820.2020.1761835
  2. Chaurasiya R, Jain D. A New Algorithm on Pythagorean Fuzzy-Based Multi-Criteria Decision-Making and Its Application. Iranian Journal of Science and Technology, Transactions of Electrical Engineering. 2023;47(3):871–886. Available from: https://doi.org/10.1007/s40998-023-00600-1
  3. Salih MM, Al-Qaysi ZT, Shuwandy ML, Ahmed MA, Hasan KF, Muhsen YR. A new extension of fuzzy decision by opinion score method based on Fermatean fuzzy: A benchmarking COVID-19 machine learning methods. Journal of Intelligent & Fuzzy Systems. 2022;43(3):3549–3559. Available from: https://doi.org/10.3233/JIFS-220707
  4. Cui FBB, You XYY, Shi H, Liu HCC. Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach. Mathematical Problems in Engineering. 2018;2018:1–12. Available from: https://doi.org/10.1155/2018/9262067
  5. Roszkowska E, Kusterka-Jefmańska M, Jefmański B. Intuitionistic fuzzy TOPSIS as a method for assessing socioeconomic phenomena on the basis of survey data. Entropy. 2021;23(5). Available from: https://doi.org/10.3390/math9192440
  6. Jefmański B, Jajuga K, Batóg J. Intuitionistic Fuzzy Synthetic Measure for Ordinal Data. In: Studies in Classification, Data Analysis, and Knowledge Organization. (pp. 53-72) Springer International Publishing. 2020.
  7. Jefmański B, Roszkowska E, Kusterka-Jefmańska M. Intuitionistic Fuzzy Synthetic Measure on the Basis of Survey Responses and Aggregated Ordinal Data. Entropy. 2021;23(12):1636. Available from: https://doi.org/10.3390/e23121636
  8. Zadeh L. Fuzzy sets. Information and Control. 1965;8(3):338–353. Available from: https://doi.org/10.1016/S0019-9958(65)90241-X
  9. Atanassov KT. Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems. 1986;20(86):80034–80037. Available from: https://doi.org/10.1016/S0165-0114(86)80034-3
  10. Xu Z. Intuitionistic fuzzy aggregation operators. IEEE Transactions on fuzzy systems. 2007;15(6):1179–1187. Available from: https://doi.org/10.1109/TFUZZ.2006.890678
  11. Liu X, Kim HS, Feng F, Alcantud JCR. Centroid Transformations of Intuitionistic Fuzzy Values Based on Aggregation Operators. Mathematics. 2018;6(11):215. Available from: https://doi.org/10.3390/math6110215
  12. Zeng W, Li D, Yin Q. Distance and similarity measures of Pythagorean fuzzy sets and their applications to multiple criteria group decision making. International Journal of Intelligent Systems. 2018;33(11):2236–2254. Available from: https://doi.org/10.1002/int.22027
  13. Feng F, Fujita H, Ali MI, Yager RR, Liu X. Another View on Generalized Intuitionistic Fuzzy Soft Sets and Related Multiattribute Decision Making Methods. IEEE Transactions on Fuzzy Systems. 2019;27(3):474–488. Available from: https://doi.org/10.1109/TFUZZ.2018.2860967
  14. Yager RR. Pythagorean Membership Grades in Multicriteria Decision Making. IEEE Transactions on Fuzzy Systems. 2014;22(4):958–965. Available from: https://doi.org/10.1109/TFUZZ.2013.2278989
  15. Pérez-Domínguez L, Rodríguez-Picón LA, Alvarado-Iniesta A, Cruz DL, Xu Z. MOORA under Pythagorean fuzzy set for multiple criteria decision making. Complexity. 2018. Available from: https://fatcat.wiki/release/issiudxstjexhl5xa7qw7h6e2u
  16. Zhang X. A Novel Approach Based on Similarity Measure for Pythagorean Fuzzy Multiple Criteria Group Decision Making. International Journal of Intelligent Systems. 2016;31(6):593–611. Available from: https://doi.org/10.1002/int.21796
  17. Wu SJJ, Wei GWW. Pythagorean fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. International Journal of Knowledge-based and Intelligent Engineering Systems. 2017;21(3):189–201. Available from: https://doi.org/10.3233/KES-170363
  18. Maggino F, Ruviglioni E. Obtaining weights: from objective to subjective approaches in view of more participative methods in the construction of composite indicators. Proceedings NTTS: new techniques and technologies for statistics. 2009;p. 37–46. Available from: https://link.springer.com/article/10.1007/s11205-017-1832-9


© 2023 Kavitha & Hepzibah. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


Subscribe now for latest articles and news.