Probabilistic linguistic TODIM approach for multiple attribute decision-making
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2017/08/10
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Journal
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Indian UGC (journal)
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Refrences30
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Citations64
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Peide Liu ORCID (unauthenticated)
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Xinli You
Cite
Liu, Peide, and Xinli You. “Probabilistic Linguistic TODIM Approach for Multiple Attribute Decision-Making”. Granular Computing, vol. 2, no. 4, 2017, pp. 333-42, https://doi.org/10.1007/s41066-017-0047-4.
Liu, P., & You, X. (2017). Probabilistic linguistic TODIM approach for multiple attribute decision-making. Granular Computing, 2(4), 333-342. https://doi.org/10.1007/s41066-017-0047-4
Liu P, You X. Probabilistic linguistic TODIM approach for multiple attribute decision-making. Granular Computing. 2017;2(4):333-42.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
Cybernetics
Information theory
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| 10.1109/TCYB.2015.2413894 | IEEE Transactions on Cybernetics |
| 2016 | |
| Managing multi-granularity linguistic information in qualitative group decision making: an overview | Granular Computing |
| 138 | 2016 |
| A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of a linguistic term for computing with words | Granular Computing |
| 114 | 2016 |
| Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making | International Journal of Computational Intelligence Systems |
| 70 | 2015 |
| 10.1109/TFUZZ.2013.2245136 | IEEE Transactions on Fuzzy Systems |
| 2014 |
Refrences Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 18
is the most frequently represented among the references in this article. It primarily includes studies from IEEE Transactions on Fuzzy Systems The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Data literacy evaluation of undergraduate in business majors based on probabilistic linguistic integrated EDAS method | Granular Computing |
| 2024 | |
| Analyzing Information Security Factors in Adoption of Intelligent Technologies for Medical Waste Management Systems | IEEE Transactions on Consumer Electronics |
| 2024 | |
| A novel probabilistic linguistic decision-making model based on discrete evidence fusion and attribute weight optimization | Engineering Applications of Artificial Intelligence |
| 2023 | |
| An extended Exp-TODIM method for multiple attribute decision making based on the Z-Wasserstein distance | Expert Systems with Applications |
| 50 | 2023 |
Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework | Financial Innovation |
| 8 | 2023 |
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 38
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled TOPSIS with similarity measure for MADM applied to network selection and was published in 2017. The most recent citation comes from a 2024 study titled Data literacy evaluation of undergraduate in business majors based on probabilistic linguistic integrated EDAS method. This article reached its peak citation in 2018, with 16 citations. It has been cited in 30 different journals, 23% of which are open access. Among related journals, the Information Sciences cited this research the most, with 9 citations. The chart below illustrates the annual citation trends for this article.