Details

Title

Visual methods of processing survey data in social disciplines based on fuzzy logic

Journal title

Bulletin of the Polish Academy of Sciences Technical Sciences

Yearbook

2021

Volume

69

Issue

5

Authors

Affiliation

Śmigielski, Grzegorz : Kazimierz Wielki University in Bydgoszcz, Institute of Informatics, ul. Kopernika 1, 85-074 Bydgoszcz, Poland ; Mreła, Aleksandra : Kazimierz Wielki University in Bydgoszcz, Institute of Informatics, ul. Kopernika 1, 85-074 Bydgoszcz, Poland ; Sokolov, Oleksandr : Nicolaus Copernicus University in Toruń, Faculty of Physics, Astronomy and Informatics, ul. Grudziądzka 5, 87-100 Toruń, Poland ; Nedashkovskyy, Mykoła : Kazimierz Wielki University in Bydgoszcz, Institute of Informatics, ul. Kopernika 1, 85-074 Bydgoszcz, Poland

Keywords

information system ; quality of education ; fuzzy relations ; optimistic fuzzy aggregation norm

Divisions of PAS

Nauki Techniczne

Coverage

e138812

Bibliography

  1.  A. Mrówczyńska, A. Król, and P. Czech, “Artificial immune system in planning deliveries in a short time,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 5, pp. 969–980, 2019, doi: 10.24425/bpas.2019.126630.
  2.  G. Kovacs, “Layout design for efficiency improvement and cost reduction,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 3, pp. 547–555, 2019, doi: 10.24425/bpasts.2019.129653.
  3.  A. Zaborowski, “Data processing in self-controlling enterprise processes, “ Bull. Pol. Acad Sci. Tech. Sci, vol. 67, no. 1, pp. 3–20, 2019, doi: 10.24425/bpas.2019.127333.
  4.  M.J. Cobo, A.G. López-Herrera, E. Herrera-Viedma, and F. Herrera, “An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field,” J. Infom., 5, pp. 146–166, 2011, doi: 10.1016/j.joi.2010.10.002.
  5.  V. Osińska, O. Sokolov, and A. Mreła, “Nonlinear Estimation of Similarity Between Scientists’ Disciplinary Profiles. Case Study,” ZIN Studia Informacyjne, 57(2A), pp. 12–27, 2019, doi: 10.36702/zin.467.
  6.  Law on higher education (Dz.U. 2005 nr 164 poz. 1365). [On line]. Available: http://isap.sejm.gov.pl/isap.nsf/DocDetails. xsp?id=WDU20051641365. (Accessed: 30 Jun. 2019) [in Polish].
  7.  R. Biswas, “An application of fuzzy sets in students’ evaluation,” Fuzzy Sets Syst., vol. 74, no. 2, pp. 187–194, 1995, doi: 10.1016/0165- 0114(95)00063-Q.
  8.  S.M. Chen and C.H. Lee, “New methods for students’ evaluating using fuzzy sets,” Fuzzy Sets Syst., vol. 104, no. 2, pp. 209–2018, 1999.
  9.  J. Ma and D. Zhou, “Fuzzy set approach to the assessment of students-centered learning,” IEEE Trans. Educ., vol. 43, no. 2, pp. 237–241, 2000, doi: 10.1109/13.848079.
  10.  D. Molodsov, “Soft Set Theory – First Results,” Comput. Math. Appl., vol. 37, pp. 19–31, 1999, doi: 10.1016/S0898-1221(99)00056-5.
  11.  B. Ahmad and A. Kharal, “On Fuzzy Soft Sets,” Adv. Fuzzy Syst., vol. 2009, no. 4–9, pp. 1–6, 2019, doi: 10.1155/2009/586507.
  12.  P. Majumdar and S.K. Samanta, “A Generalized Fuzzy Soft Set Based Student Ranking System,” Int. J. Adv. Soft Comput. Appl., vol. 3, no. 3, pp. 42‒51, Nov. 2011. [Online]. Available: http://home.ijasca.com/data/documents/A-Generalised-Fuzzy-Soft-Set.pdf (Accessed: 20 Aug. 2019).
  13.  S. Weon and J. Kim, “Learning achievement evaluation strategy using fuzzy membership function,” in Proc. 31st ASEE/IEEE Frontiers in Education Conference, Reno, NV, USA, 2001, pp. T3A-19, doi: 10.1109/FIE.2001.963904. [Online]. Available: http://archive.fie- conference.org/fie2001/papers/1215.pdf (Accessed: 21 Aug. 2019).
  14.  S.M. Bai and S.M. Chen, “Evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules,” Expert Syst. Appl., vol. 34, no. 1, pp. 399–410, 2008, doi: 10.1016/j.eswa.2006.09.010.
  15.  F. Dayan, M. Zulqarnain, and N. Hassan, “A Ranking Method for Students of Different Socio Economic Backgrounds Based on Generalized Fuzzy Soft Sets,” Int. J. Sci. Res. (IJSR), vol. 6, no 9, pp. 691‒694, Sep. 2017, [Online] Available: https://www.ijsr.net/search_index_ results_paperid.php?id=ART20176512. (Accessed: 20 Aug. 2019).
  16.  A. Mreła, O. Sokolov, and W. Urbaniak, “The method of learning outcomes assessment based on fuzzy relations,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 3, pp. 527‒533, 2019, doi: 10.24425/bpasts.2019.129651.
  17.  Report on the quality of education in Adam Mickiewicz University in Poznań. [Online]. Available: http://brjk.amu.edu.pl/badanie-jakosci- ksztalcenia/badanie-jakosci-ksztalcenia-na-uam (Accessed: 30 Jun. 2019) [in Polish].
  18.  Report on the quality of education at Warsaw University of Technology, Faculty of Materials Science and Engineering. [Online]. Available: https://www.wim.pw.edu.pl/content/download/1668/14211/file/ankietyzacja.pdf (Accessed: 30 Jun. 2019) [in Polish].
  19.  Report on the quality of education at Kazimierz Wielki University in Bydgoszcz, [Online]. Available: https://www.ukw.edu.pl/download/34273/raport_oceny_ankietyzacja_2017_2018_ukw_bydgoszcz.pdf (Accessed: 30 Jun. 2019) [in Polish].
  20. [20]  L.A. Zadeh, “Fuzzy sets,” Inf.Control, vol. 8, no. 3, pp. 338–353, 1965, doi: 10.1016/S0019-9958(65)90241-X.
  21.  L.A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning –1,” Inf. Sci., vol. 8, pp. 199–249, 1975, doi: 10.1016/0020-0255(75)90036-5.
  22.  L. Rutkowski, Methods and techniques of artificial intelligence, PWN, Warsaw, pp. 1–452, 2012, [in Polish].
  23.  O. Sokolov, W. Osińska, A. Mreła, and W. Duch, “Modeling of Scientific Publications Disciplinary Collocation Based on Optimistic Fuzzy Aggregation Norms,” in Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018., eds. J. Światek, L. Borzemski and Z. Wilmowska, Advances in Intelligent Systems and Computing. Information Systems Architecture and Technology Part II, vol. 853, pp. 145–156, 2019, doi: 10.1007/978-3-319-99996-8.
  24.  L.J.P. Van der Maaten and G.E. Hinton, “Visualizing data using t-SNE,” J. Mach. Learn. Res., vol. 9, pp. 2579–2605, Nov. 2008, [Online]. Available: https://research.tilburguniversity.edu/en/publications/visualizing-high-dimensional-data-using-t-sne (Accessed: 21 Jun. 2019).
  25.  C.L. Hwang and K. Yoon, “Methods for multiple attribute decision making”, in Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, vol. 186. Springer, Berlin, Heidelberg, doi: 10.1007/978-3-642-48318-9_3.

Date

15.09.2021

Type

Article

Identifier

DOI: 10.24425/bpasts.2021.138812
×