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Abstract

Multicriteria group decision making (MCDM) approach using fuzzy set for Information System (IS) Project Selection evaluation and selection is represented in this paper. The selection of the projects is also considered as the evaluating process for each project’s idea and the idea which has the highest priority has been chosen. In the competitive environment evaluating and selecting the right and reliable IS Projects can be considered as the main factor for the corporate competition ability. Evaluation imprecision which is modeled by trapezoidal fuzzy type 2 set characterizes linguistic term. Information technologies project selection problem is represented to indicate the approach sensitivity with information processing efficiency, system reliability, cost of implementation and three alternatives.

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References

  1. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  MATH  Google Scholar 

  2. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning – I. Inform. Sci. 8(3), 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  3. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning-1. Inform. Sci. 8, 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  4. Gardashova, L.A.: Application of operational approaches to solving decision making problem using Z-numbers. J. Appl. Math.. 5(9), 1323–1334 (2014). https://doi.org/10.4236/am.2014.59125

    Article  Google Scholar 

  5. Aliev, R.A., Guirimov, B.G., Huseynov, O.H., Aliyev, R.R.: A consistency-driven approach to construction of Z-number-valued pairwise comparison matrices. Iran J. Fuzzy Syst. 18(4), 37–49 (2021)

    MathSciNet  MATH  Google Scholar 

  6. Huseynov, O.H., Adilova, N.E.: Multi-criterial optimization problem for fuzzy if-then rules. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M., Sadikoglu, F.M. (eds.) ICAFS 2020. AISC, vol. 1306, pp. 80–88. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-64058-3_10

  7. Huseynova, N.F.: Decision making on tourism by using natural language processing. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M., Sadikoglu, F.M. (eds.) ICSCCW 2021. LNNS, vol. 362, pp. 741–747. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-92127-9_98

  8. Oztaysi, B.: A Group decision making approach using interval type-2 fuzzy AHP for enterprise information system project selection. J. Multiple-Val. Logic Soft Comput. 24(5–6), 475–500 (2015)

    Google Scholar 

  9. Dadasheva, A.N.: Analysis of consistency of pairwise comparison matrix with fuzzy type-2 elements. Lect. Notes Netw. Syst. 362, 324–330 (2022)

    Article  Google Scholar 

  10. Sadikoglu, G., Dovlatova, Kh. J.: Investigation of preference knowledge of decision maker on consumer buying behaviour. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M., Sadikoglu, F. (eds.) 10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions-ICSCCW-2019, AISC, vol. 1095, pp. 613–621. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-35249-3_78

  11. Aliyeva, K.: Multifactor personnel selection by the fuzzy TOPSIS method. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Mo., Jamshidi, Sadikoglu, F.M. (eds.) ICAFS 2018. AISC, vol. 896, pp. 478–483. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-04164-9_64

  12. Gardashova, L.A.: Z-number based TOPSIS method in multi-criteria decision making. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Mo., Jamshidi, Sadikoglu, F.M. (eds.) ICAFS 2018. AISC, vol. 896, pp. 42–50. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-04164-9_10

  13. Aliyeva, K.R.: Facility location problem by using Fuzzy TOPSIS Method. B-quadrat verlags, pp. 55–59. Uzbekistan (2018). https://doi.org/10.34920/2018.4-5.55-59

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Correspondence to Aygul Dadasheva .

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Dadasheva, A. (2023). Multicriteria Group Decision Making on Information System Project Selection Using Type-2 Fuzzy Set. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M.B., Sadikoglu, F. (eds) 15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022. ICAFS 2022. Lecture Notes in Networks and Systems, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-031-25252-5_19

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