EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 41 / No 6 (Decembre 2023) JNWPU, 41 6 (2023) 1209-1220 References
Open Access
Issue
JNWPU
Volume 41, Number 6, Decembre 2023
Page(s) 1209 - 1220
DOI https://doi.org/10.1051/jnwpu/20234161209
Published online 26 February 2024
  1. ZADEH L A. Fuzzy sets[J]. Information and Control, 1965, 8(3): 338–356. [Article] [Google Scholar]
  2. TORRA V. Hesitant fuzzy sets[J]. International Journal of Intelligent Systems, 2010, 25(6): 529–539 [Google Scholar]
  3. ZHU Bin. Decison making methods and applications based on preference relations[D]. Nanjing: Southeast University, 2014 (in Chinese) [Google Scholar]
  4. ZHANG S, XU Z S, HE Y. Operations and integrations of probabilistic hesitant fuzzy information in decision making[J]. Information Fusion, 2017, 38: 1–11. [Article] [CrossRef] [Google Scholar]
  5. PARK J, PARK Y, SON M. Hesitant probabilistic fuzzy information aggregation using Einstein operations[J]. Information, 2018, 9(9): 226. [Article] [CrossRef] [Google Scholar]
  6. LI J, WANG Z X. Multi-attribute decision making based on prioritized operators under probabilistic hesitant fuzzy environments[J]. Soft Computing, 2019, 23(11): 3853–3868. [Article] [CrossRef] [Google Scholar]
  7. ZHOU W, XU Z S. Group consistency and group decision making under uncertain probabilistic hesitant fuzzy preference environment[J]. Information Sciences, 2017, 414: 276–288. [Article] [CrossRef] [Google Scholar]
  8. LI J, WANG Z X. Consensus building for probabilistic hesitant fuzzy preference relations with expected additive consistency[J]. International Journal of Fuzzy Systems, 2018, 20(5): 1495–1510. [Article] [CrossRef] [Google Scholar]
  9. LI J, WANG J Q. Multi-criteria decision-making with probabilistic hesitant fuzzy information based on expected multiplicative consistency[J]. Neural Computing and Applications, 2019, 31(12): 8897–8915. [Article] [CrossRef] [Google Scholar]
  10. HE Y, XU Z S. Multi-attribute decision making methods based on reference ideal theory with probabilistic hesitant information[J]. Expert Systems with Applications, 2019, 118: 459–469. [Article] [CrossRef] [Google Scholar]
  11. WANG Z X, LI J. Correlation coefficients of probabilistic hesitant fuzzy elements and their applications to evaluation of the alternatives[J]. Symmetry, 2017, 9(11): 259. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  12. WU W, LI Y, NI Z, et al. Probabilistic interval-valued hesitant fuzzy information aggregation operators and their application to multi-attribute decision making[J]. Algorithms, 2018, 11(8): 120. [Article] [CrossRef] [Google Scholar]
  13. HAO Z N, XU Z S, ZHAO H, et al. Probabilistic dual hesitant fuzzy set and its application in risk evaluation[J]. Knowledge-Based Systems, 2017, 127: 16–28. [Article] [CrossRef] [Google Scholar]
  14. GAO J, XU Z S, LIAO H C. A dynamic reference point method for emergency response under hesitant probabilistic fuzzy environment[J]. International Journal of Fuzzy Systems, 2017, 19(5): 1261–1278. [Article] [CrossRef] [Google Scholar]
  15. SU Z, XU Z S, ZHAO H, et al. Entropy Measures for Probabilistic Hesitant Fuzzy Information[J]. IEEE Access, 2019, 7: 65714–65727. [Article] [CrossRef] [Google Scholar]
  16. FANG Bing, HAN Bing, WEN Chuanhua. Probabilistic hesitant fuzzy group decision-making based on new distance measure[J]. Control and Decision, 2022, 37(3): 729–736 (in Chinese) [Google Scholar]
  17. XU Z S, ZHOU W. Consensus building with a group of decision makers under the hesitant probabilistic fuzzy environment[J]. Fuzzy Optimization and Decision Making, 2017, 16(4): 481–503. [Article] [CrossRef] [Google Scholar]
  18. Gao J, Xu Z, Liao H. A dynamic reference point method for emergency response under hesitant probabilistic fuzzy environment[J]. International Journal of Fuzzy Systems, 2017, 19(5): 1261–1278. [Article] [CrossRef] [Google Scholar]
  19. QIU Wanhua. Management decision and applied entropy[M]. Beijing: China Machine Press, 2002 (in Chinese) [Google Scholar]
  20. ZHANG X, XU Z S. The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment[J]. Knowledge-Based Systems, 2014, 61(1): 48–58 [CrossRef] [Google Scholar]
  21. WANG Yingming, QUE Cuiping, LAN Yixin. Hesitant fuzzy TOPSIS multi-attribute decision method based on prospect theory[J]. Control and Decision, 2017, 32(5): 864–870 (in Chinese) [Google Scholar]
  22. ZHU Feng, XU Jichao, LIU Yumin, et al. Probabilistic hesitant fuzzy multi-attribute decision method based on signed distance and cross entropy[J]. Control and Decision, 2020, 35(8): 1977–1986 (in Chinese) [Google Scholar]
  23. LIU Yumin, ZHU Feng, JIN Linlin. Multi-attribute decision-making method based on probabilistic hesitant fuzzy entropy[J]. Control and Decision, 2019, 34(4): 861–870 (in Chinese) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.