Log in

Relevant bibliographies by topics / Fuzzy Measures / Journal articles

Journal articles on the topic 'Fuzzy Measures'

To see the other types of publications on this topic, follow the link: Fuzzy Measures.

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Fuzzy Measures.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Congxin Wu, Deli Zhang, Caimei Guo, and Cong Wu. "Fuzzy number fuzzy measures and fuzzy integrals. (I). Fuzzy integrals of functions with respect to fuzzy number fuzzy measures." Fuzzy Sets and Systems 98, no. 3 (September 1998): 355–60. http://dx.doi.org/10.1016/s0165-0114(96)00394-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Squillante, Massimo, and Aldo G. S. Ventre. "Generating fuzzy measures." Journal of Mathematical Analysis and Applications 165, no. 2 (April 1992): 550–55. http://dx.doi.org/10.1016/0022-247x(92)90058-l.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Glass, David H. "Fuzzy confirmation measures." Fuzzy Sets and Systems 159, no. 4 (February 2008): 475–90. http://dx.doi.org/10.1016/j.fss.2007.07.018.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Cutello, Vincenzo, and Javier Montero. "Fuzzy rationality measures." Fuzzy Sets and Systems 62, no. 1 (February 1994): 39–54. http://dx.doi.org/10.1016/0165-0114(94)90071-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Sancho-Royo, A., and J. L. Verdegay. "Fuzzy coherence measures." International Journal of Intelligent Systems 20, no. 1 (January 2005): 1–11. http://dx.doi.org/10.1002/int.20050.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

de Glas, Michel. "Fuzzy σ-fields and fuzzy measures." Journal of Mathematical Analysis and Applications 124, no. 1 (May 1987): 281–89. http://dx.doi.org/10.1016/0022-247x(87)90039-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Caimei Guo, Deli Zhang, and Congxin Wu. "Fuzzy-valued fuzzy measures and generalized fuzzy integrals." Fuzzy Sets and Systems 97, no. 2 (July 1998): 255–60. http://dx.doi.org/10.1016/s0165-0114(96)00276-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Maturo, Antonio. "Fuzzy measures and coherent join measures." International Journal of Intelligent Systems 26, no. 12 (October 11, 2011): 1196–205. http://dx.doi.org/10.1002/int.20512.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Wu, Congxin, Deli Zhang, Bokan Zhang, and Caimei Guo. "Fuzzy number fuzzy measures and fuzzy integrals. (II). Fuzzy integrals of fuzzy-valued functions with respect to fuzzy number fuzzy measures on fuzzy sets." Fuzzy Sets and Systems 101, no. 1 (January 1999): 137–41. http://dx.doi.org/10.1016/s0165-0114(97)00041-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

CALVO, T., J. MARTIN, G. MAYOR, and J. TORRENS. "BALANCED DISCRETE FUZZY MEASURES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 08, no. 06 (December 2000): 665–76. http://dx.doi.org/10.1142/s0218488500000484.

Full text

Abstract:

First a balancing property on a fuzzy measure is introduced. After that, the conditions of when an additive fuzzy measure is balanced are given and similar results are presented for 0-1 and S–decomposable fuzzy measures where S is a continuous t–conorm. Moreover, the concept of distance between two additive fuzzy measures is presented and some results related to the distance and the balancing property are developed.

APA, Harvard, Vancouver, ISO, and other styles

11

Honda, Aoi, and Yoshiaki Okazaki. "Identification of Fuzzy Measures with Distorted Probability Measures." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 5 (September 20, 2005): 467–76. http://dx.doi.org/10.20965/jaciii.2005.p0467.

Full text

Abstract:

We consider the identification of fuzzy measures using a class of distorted probabilities – a scale transformation of probabilities. A fuzzy measure, which is a nonadditive set function with a high degree of freedom, enables us to express complicated interactions among evaluative items. Because of the high degree of freedom, however, it is difficult to identify all of the values μ(A) for every event A from known data μ(B), B ∈ A, where A is generally a small subclass of events. In this paper, we classify fuzzy measures by introducing “type,” and propose an identifying fuzzy measures using a classified class of distorted probabilities.

APA, Harvard, Vancouver, ISO, and other styles

12

Phong, Pham Hong, and Vu Thi Hue. "On Integration Linguistic Factors to Fuzzy Similarity Measures and Intuitionistic Fuzzy Similarity Measures." International Journal of Synthetic Emotions 10, no. 1 (January 2019): 1–37. http://dx.doi.org/10.4018/ijse.2019010101.

Full text

Abstract:

The article is concerned with integrating linguistic elements into fuzzy similarity measures and intuitionistic fuzzy similarity measure. Some new concepts are proposed: a fuzzy linguistic value (FLv), a fuzzy linguistic vector (FLV), an intuitionistic fuzzy linguistic vector (ILV) and similarity measures. The proposed measures are used to build classification algorithms. As predicted theoretically, experiments show that with the same type of similarity measures, the linguistic-aggregated similarity measures produce better results in classification problems.

APA, Harvard, Vancouver, ISO, and other styles

13

Suzuki, Hisakichi. "Atoms of fuzzy measures and fuzzy integrals." Fuzzy Sets and Systems 41, no. 3 (June 1991): 329–42. http://dx.doi.org/10.1016/0165-0114(91)90136-e.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

SIMS, JOHN R., and WANG ZHENYUAN. "FUZZY MEASURES AND FUZZY INTEGRALS: AN OVERVIEW." International Journal of General Systems 17, no. 2-3 (June 1990): 157–89. http://dx.doi.org/10.1080/03081079008935106.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Yager, Ronald R. "On Viewing Fuzzy Measures as Fuzzy Subsets." IEEE Transactions on Fuzzy Systems 24, no. 4 (August 1, 2016): 811–18. http://dx.doi.org/10.1109/tfuzz.2015.2486808.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Suzuki, Hisakichi. "On fuzzy measures defined by fuzzy integrals." Journal of Mathematical Analysis and Applications 132, no. 1 (May 1988): 87–101. http://dx.doi.org/10.1016/0022-247x(88)90045-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

MIRANDA, PEDRO, MICHEL GRABISCH, and PEDRO GIL. "p-SYMMETRIC FUZZY MEASURES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10, supp01 (December 2002): 105–23. http://dx.doi.org/10.1142/s0218488502001867.

Full text

Abstract:

In this paper we propose a generalization of the concept of symmetric fuzzy measure based in a decomposition of the universal set in what we have called subsets of indifference. Some properties of these are studied, as well as their Choquet integral. Finally, a degree of interaction between the subsets of indifference is defined.

APA, Harvard, Vancouver, ISO, and other styles

18

Mesiar, Radko, and Endre Pap. "Fuzzy measures and integrals." Fuzzy Sets and Systems 102, no. 3 (March 1999): 361. http://dx.doi.org/10.1016/s0165-0114(98)00210-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Mesiar, Radko. "Fuzzy measures and integrals." Fuzzy Sets and Systems 156, no. 3 (December 2005): 365–70. http://dx.doi.org/10.1016/j.fss.2005.05.033.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Lamata, M. T., and S. Moral. "Classification of fuzzy measures." Fuzzy Sets and Systems 33, no. 2 (November 1989): 243–53. http://dx.doi.org/10.1016/0165-0114(89)90245-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Wu, Congxin, and Xuekun Ren. "Fuzzy measures and discreteness." Discrete Mathematics 308, no. 21 (November 2008): 4839–45. http://dx.doi.org/10.1016/j.disc.2007.09.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Squillante, Massimo, and Aldo G. S. Ventre. "Fuzzy measures and convergence." Fuzzy Sets and Systems 25, no. 2 (February 1988): 251–57. http://dx.doi.org/10.1016/0165-0114(88)90191-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Xu, Zeshui. "Fuzzy ordered distance measures." Fuzzy Optimization and Decision Making 11, no. 1 (November 17, 2011): 73–97. http://dx.doi.org/10.1007/s10700-011-9113-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Mesiar, Radko. "Possibility measures, integration and fuzzy possibility measures." Fuzzy Sets and Systems 92, no. 2 (December 1997): 191–96. http://dx.doi.org/10.1016/s0165-0114(97)00169-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Santos, Helida, Inés Couso, Benjamin Bedregal, Zdenko Takáč, Mária Minárová, Alfredo Asiaın, Edurne Barrenechea, and Humberto Bustince. "Similarity measures, penalty functions, and fuzzy entropy from new fuzzy subsethood measures." International Journal of Intelligent Systems 34, no. 6 (January 29, 2019): 1281–302. http://dx.doi.org/10.1002/int.22096.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Haryati, Anisa Eka, and Sugiyarto Surono. "COMPARATIVE STUDY OF DISTANCE MEASURES ON FUZZY SUBTRACTIVE CLUSTERING." MEDIA STATISTIKA 14, no. 2 (December 12, 2021): 137–45. http://dx.doi.org/10.14710/medstat.14.2.137-145.

Full text

Abstract:

Clustering is a data analysis process which applied to classify the unlabeled data. Fuzzy clustering is a clustering method based on membership value which enclosing set of fuzzy as a measurement base for classification process. Fuzzy Subtractive Clustering (FSC) is included in one of fuzzy clustering method. This research applies Hamming distance and combined Minkowski Chebysev distance as a distance parameter in Fuzzy Subtractive Clustering. The objective of this research is to compare the output quality of the cluster from Fuzzy Subtractive Clustering by using Hamming distance and combine Minkowski Chebysev distance. The comparison of the two distances aims to see how well the clusters are produced from two different distances. The data used is data on hypertension. The variables used are age, gender, systolic pressure, diastolic pressure, and body weight. This research shows that the Partition Coefficient value resulted on Fuzzy Subtractive Clustering by applying combined Minkowski Chebysev distance is higher than the application of Hamming distance. Based on this, it can be concluded that in this study the quality of the cluster output using the combined Minkowski Chebysev distance is better.

APA, Harvard, Vancouver, ISO, and other styles

27

Mishra, Arunodaya Raj, Divya Jain, and D. S. Hooda. "On fuzzy distance and induced fuzzy information measures." Journal of Information and Optimization Sciences 37, no. 2 (March 3, 2016): 193–211. http://dx.doi.org/10.1080/02522667.2015.1103034.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Liu, Shiang-Tai, and Chiang Kao. "Fuzzy measures for correlation coefficient of fuzzy numbers." Fuzzy Sets and Systems 128, no. 2 (June 2002): 267–75. http://dx.doi.org/10.1016/s0165-0114(01)00199-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Liu, Shiang-Tai. "Fuzzy measures for profit maximization with fuzzy parameters." Journal of Computational and Applied Mathematics 236, no. 6 (October 2011): 1333–42. http://dx.doi.org/10.1016/j.cam.2011.08.019.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Congxin, Wu, and Sun Bo. "Pseudo-atoms of fuzzy and non-fuzzy measures." Fuzzy Sets and Systems 158, no. 11 (June 2007): 1258–72. http://dx.doi.org/10.1016/j.fss.2006.12.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Bhutani, Kiran R., and Azriel Rosenfeld. "Dissimilarity measures between fuzzy sets or fuzzy structures." Information Sciences 152 (June 2003): 313–18. http://dx.doi.org/10.1016/s0020-0255(03)00076-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

LIU, SHIANG-TAI. "FUZZY MEASURES FOR FUZZY SIGNAL-TO-NOISE RATIOS." Cybernetics and Systems 36, no. 2 (January 18, 2005): 151–63. http://dx.doi.org/10.1080/01969720590897161.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Dumitrescu, D. "Fuzzy Measures and the Entropy of Fuzzy Partitions." Journal of Mathematical Analysis and Applications 176, no. 2 (July 1993): 359–73. http://dx.doi.org/10.1006/jmaa.1993.1220.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Gupta, Priti, and Santosh Kumari. "On Bounds For Weighted Fuzzy Mean Difference-Divergence Measures." International Journal of Scientific Research 3, no. 6 (June 1, 2012): 239–49. http://dx.doi.org/10.15373/22778179/june2014/78.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Xue, Yige, and Yong Deng. "Extending Set Measures to Orthopair Fuzzy Sets." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 30, no. 01 (February 2022): 63–91. http://dx.doi.org/10.1142/s0218488522500040.

Full text

Abstract:

Yager have proposed the extending set measures to Pythagorean fuzzy sets, which is able to efficiently solve the problems of uncertain information representation in Pythagorean fuzzy environment. However, the Pythagorean fuzzy sets represent a limited range of fields, while the q-rung orthopair fuzzy sets can represent many fuzzy sets, including the Pythagorean fuzzy sets, Fermatean fuzzy sets, and intuitionistic fuzzy sets. In order to extend the extending set measures to Pythagorean fuzzy sets to a broader range, the paper proposes the extending set measures to orthopair fuzzy sets, which can extend the extending set measures to Pythagorean fuzzy sets to q-rung orthopair fuzzy environment. The extending set measures to orthopair fuzzy sets combined with level sets, measure, principle extension and Choquet Integral, which can greatly extend the ability of representing unknown information and processing unknown information. If the q-rung orthopair fuzzy sets degenerate into to Pythagorean fuzzy sets, then the extending set measures to orthopair fuzzy sets will be generated as the extending set measures to Pythagorean fuzzy sets. Numerical examples are designed to prove the effectiveness of the proposed models and the experimental results demonstrate that the proposed method can extend the extending set measures to Pythagorean fuzzy sets to q-rung orthopair fuzzy environment successfully and solve issues of decision making under q-rung orthopair fuzzy environment effectively.

APA, Harvard, Vancouver, ISO, and other styles

36

MARICHAL, JEAN-LUC, and MARC ROUBENS. "ENTROPY OF DISCRETE FUZZY MEASURES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 08, no. 06 (December 2000): 625–40. http://dx.doi.org/10.1142/s0218488500000460.

Full text

Abstract:

The concept of entropy of a discrete fuzzy measure has been recently introduced in two different ways. A first definition was proposed by Marichal in the aggregation framework, and a second one by Yager in the framework of uncertain variables. We present a comparative study between these two proposals and point out their properties. We also propose a definition for the entropy of an ordinal fuzzy measure, that is, a fuzzy measure taking its values in an ordinal scale in the sense of measurement theory.

APA, Harvard, Vancouver, ISO, and other styles

37

Kobza, Vladimír. "Divergence measures on intuitionistic fuzzy sets." Notes on Intuitionistic Fuzzy Sets 28, no. 4 (December 12, 2022): 413–27. http://dx.doi.org/10.7546/nifs.2022.28.4.413-427.

Full text

Abstract:

The basic study of fuzzy sets theory was introduced by Lotfi Zadeh in 1965. Many authors investigated possibilities how two fuzzy sets can be compared and the most common kind of measures used in the mathematical literature are dissimilarity measures. The previous approach to the dissimilarities is too restrictive, because the third axiom in the definition of dissimilarity measure assumes the inclusion relation between fuzzy sets. While there exist many pairs of fuzzy sets, which are incomparable to each other with respect to the inclusion relation. Therefore we need some new concept for measuring a difference between fuzzy sets so that it could be applied for arbitrary fuzzy sets. We focus on the special class of so called local divergences. In the next part we discuss the divergences defined on more general objects, namely intuitionistic fuzzy sets. In this case we define the local property modified to this object. We discuss also the relation of usual divergences between fuzzy sets to the divergences between intuitionistic fuzzy sets.

APA, Harvard, Vancouver, ISO, and other styles

38

MIRANDA, PEDRO, and MICHEL GRABISCH. "OPTIMIZATION ISSUES FOR FUZZY MEASURES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 07, no. 06 (December 1999): 545–60. http://dx.doi.org/10.1142/s0218488599000477.

Full text

Abstract:

In this paper, we address the problem of identification of fuzzy measures through different representations, namely the Möbius, the Shapley and the Banzhaf interaction representations. In the first part of the paper, we recall the main results concerning these representations, and give a simple algorithm to compute them. Then we determine the bounds of the Möbius and the interaction representations for fuzzy measures. Lastly, the identification of fuzzy measures by minimizing a quadratic error criterion is addressed. We give expressions of the quadratic program for all the considered representations, and study the uniqueness of the solution.

APA, Harvard, Vancouver, ISO, and other styles

39

MESIAR, RADKO. "k–ORDER ADDITIVE FUZZY MEASURES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 07, no. 06 (December 1999): 561–68. http://dx.doi.org/10.1142/s0218488599000489.

Full text

Abstract:

A generalization of k-order additive discrete fuzzy measures recently introduced by Grabisch is shown. k-order additive fuzzy measures on general spaces are introduced. Connection of the proposed generalization with the general Möbius transform of Shafer is shown. General evaluation formula for the Choquet integral is given. Further generalizations concerning the type of applied arithmetics are proposed.

APA, Harvard, Vancouver, ISO, and other styles

40

Çetkin, Vildan. "On measures of parameterized fuzzy compactness." Filomat 34, no. 9 (2020): 2927–38. http://dx.doi.org/10.2298/fil2009927c.

Full text

Abstract:

In the present study, the parameterized degree of compactness of a lattice valued fuzzy soft set is described in a fuzzy soft topological space. The extended versions of the basic compactness properties known in general topology are investigated for the given notion and some further characterizations of parameterized degree of fuzzy compactness are specified. In addition, a generalized version of Tychonoff Theorem is proved in the product fuzzy soft topological space.

APA, Harvard, Vancouver, ISO, and other styles

41

DING, Shi-Fei, Hong ZHU, Xin-Zheng XU, and Zhong-Zhi SHI. "Entropy-Based Fuzzy Information Measures." Chinese Journal of Computers 35, no. 4 (November 16, 2012): 796–801. http://dx.doi.org/10.3724/sp.j.1016.2012.00796.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

FUJIMOTO, Katsushige. "Interaction indices for fuzzy measures." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 16, no. 4 (2004): 303–10. http://dx.doi.org/10.3156/jsoft.16.303.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

R. Yager, Ronald. "Uncertainty modeling using fuzzy measures." Knowledge-Based Systems 92 (January 2016): 1–8. http://dx.doi.org/10.1016/j.knosys.2015.10.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Mesiar, R., A. Mesiarová-Zemánková, and L’ Valášková. "Basic generated universal fuzzy measures." International Journal of Approximate Reasoning 46, no. 3 (December 2007): 447–57. http://dx.doi.org/10.1016/j.ijar.2006.12.012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Delgado, M., and S. Moral. "Upper and lower fuzzy measures." Fuzzy Sets and Systems 33, no. 2 (November 1989): 191–200. http://dx.doi.org/10.1016/0165-0114(89)90240-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Sgarro, Andrea. "Fuzziness measures for fuzzy rectangles." Fuzzy Sets and Systems 34, no. 1 (January 1990): 39–45. http://dx.doi.org/10.1016/0165-0114(90)90125-p.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Jiang, Qingshan, and Hisakichi Suzuki. "Fuzzy measures on metric spaces." Fuzzy Sets and Systems 83, no. 1 (October 1996): 99–106. http://dx.doi.org/10.1016/0165-0114(95)00304-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Guo, Caimei, and Deli Zhang. "On set-valued fuzzy measures." Information Sciences 160, no. 1-4 (March 2004): 13–25. http://dx.doi.org/10.1016/j.ins.2003.07.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Yager, Ronald R. "Probability measures over fuzzy spaces." International Journal of General Systems 36, no. 3 (June 2007): 251–62. http://dx.doi.org/10.1080/03081070601058604.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Yager, R. R. "Uncertainty representation using fuzzy measures." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 32, no. 1 (2002): 13–20. http://dx.doi.org/10.1109/3477.979955.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!