The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING
Abstract
In this paper we shall develop a procedure for combining numerical and linguistic information without loss of information in the transformation processes between numerical and linguistic information, taking as base for representing the information the 2-tuple fuzzy linguistic representation model. We shall analyze the conditions to impose the linguistic term set in order to ensure that the combination procedure does not produce any loss of information. Afterwards the aggregation process will be applied to a decision procedure over a multi-attribute decision-making problem dealing with numerical and linguistic information, that is, with qualitative and quantitative attributes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1956) · Psychological Review · doi:10.1037/h0043158 · Cited by 17,812
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1994) · Psychological Review · doi:10.1037/0033-295x.101.2.343 · Cited by 17,161
The Concept of a Linguistic Variable and Its Application to Approximate Reasoning—I
Zadeh, L. A. (1975) · Information Sciences · doi:10.1016/0020-0255(75)90036-5 · Cited by 12,187
The concept of a linguistic variable and its application to approximate reasoning-III
Zadeh, L. A. (1975) · Information Sciences · doi:10.1016/0020-0255(75)90017-1 · Cited by 12,139
Multiple Attribute Decision Making: Methods and Applications
Chen, S.-J. J., Hwang, C. L., Beckmann, M. J., & Krelle, W. E. (1981) · Medical Entomology and Zoology · Cited by 8,207
Extensions of the TOPSIS for group decision-making under fuzzy environment
Chen, C.-T. (2000) · Fuzzy Sets and Systems · doi:10.1016/s0165-0114(97)00377-1 · Cited by 3,844
A 2-tuple fuzzy linguistic representation model for computing with words
Martinez, L., & Herrera, F. (2000) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.890332 · Cited by 2,662
Self-citationFuzzy Preference Modelling and Multicriteria Decision Support
Fodor, J., & Roubens, M. (1994) · Springer eBooks · doi:10.1007/978-94-017-1648-2 · Cited by 2,019
A fusion approach for managing multi-granularity linguistic term sets in decision making
Herrera, F., Herrera-Viedma, E., & Martı́nez, L. (2000) · Fuzzy Sets and Systems · doi:10.1016/s0165-0114(98)00093-1 · Cited by 795
Self-citationAn evidential reasoning approach for multiple-attribute decision making with uncertainty
Yang, J.-B., & Singh, M. G. (1994) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/21.259681 · Cited by 781
Cited by
A 2-tuple fuzzy linguistic representation model for computing with words
Martinez, L., & Herrera, F. (2000) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.890332 · Cited by 2,662
Self-citationCorrelation coefficients of hesitant fuzzy sets and their applications to clustering analysis
Chen, N., Xu, Z., & Xia, M. (2013) · Applied Mathematical Modelling · doi:10.1016/j.apm.2012.04.031 · Cited by 481
Ding, R.-X., Palomares, I., Wang, X., Yang, G.-R., Liu, B., Dong, Y., Herrera-Viedma, E., & Herrera, F. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.01.006 · Cited by 301
Self-citationPROJECTION MODELS FOR INTUITIONISTIC FUZZY MULTIPLE ATTRIBUTE DECISION MAKING
XU, Z., & HU, H. (2010) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622010003816 · Cited by 259
Kliegr, T., Bahník, Š., & Fürnkranz, J. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103458 · Cited by 139
Metadata
- Authors
- HERRERA, F., & MARTINEZ, L.
- Venue
- International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 2000-10
- Volume
- 08
- Issue
- 05
- Pages
- 539-562
- ISSN
- 0218-4885 (ISSN-L)
- 1793-6411
- OpenAlex
- W2003194756
- Cited by
- 454
- References
- 20
- FWCI
- 4.10
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING. https://app.cochat.ai/papers/10.1142/s0218488500000381
- The paper
- HERRERA, F., & MARTINEZ, L. (2000). AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. https://doi.org/10.1142/s0218488500000381
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
