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Gotowa bibliografia na temat „FUZZY INDEX”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "FUZZY INDEX"

1

Omana, Rebecca Walo. "FUZZY CONLEY INDEX AND INVARIANT FUZZY SETS." Advances in Fuzzy Sets and Systems 26, no. 2 (2021): 175–209. http://dx.doi.org/10.17654/fs026020175.

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2

BUSTINCE, H., E. BARRENECHEA, M. PAGOLA, and F. SORIA. "WEAK FUZZY S-SUBSETHOOD MEASURES: OVERLAP INDEX." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 05 (2006): 537–60. http://dx.doi.org/10.1142/s0218488506004187.

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Starting from the definitions of the weak fuzzy subsethood measure (V.R. Young, Fuzzy subsethood. Fuzzy Sets and Systems, 77 (1996) 371–384) and of strong fuzzy inclusion, (D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications, New York, Academic Press, 1980) we define weak fuzzy S-subsethood measures. We analyze their axiomatization and present various constructions obtained by aggregating implication operators with special properties. We conclude by presenting the conditions under which we can construct fuzzy entropies and overlap indices from these measures.

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3

Abdolshah, Mohammad. "Measuring Loss-Based Process Capability IndexLeand Its GenerationLe′′with Fuzzy Numbers." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/217406.

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Loss-based process capability indices are appropriate and realistic tools in order to measure the process capability. Among them, indexLeand its generationLe′′are well-known loss-based process capability indices, whose concepts are based on the worth (the opposite concept of loss). Sometimes, in order to calculateLeandLe′′there are some uncertainties in observations, so fuzzy logic can be employed to manage the uncertainties. This paper investigates fuzzification of process capability indexL~eand its generationL~e′′. In order to find the membership function of process capability indicesL~eandL~e′′, theα-cuts of fuzzy observation were employed. Then with an example of fuzzy process capability index,L~eandL~e′′were calculated and compared. Results showed that fuzzyL~e′′was more sensitive compared withL~eand was increased while the target departs (asymmetric tolerance). This example also showed that, with departure from the target, variation of fuzzyL~e′′and consequently its fuzziness were increased.

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4

Bala, Kalla Hema, and Dr B. Srinivasa Kumar. "Index Number of Multi Fuzzy Sets." International Journal of Recent Technology and Engineering (IJRTE) 8, no. 4 (2019): 2873–76. http://dx.doi.org/10.35940/ijrte.d2888.118419.

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Multi fuzzy set theory is an extension of fuzzy set theory. In this paper we developing the theory of Index number of multi fuzzy sets. This theory is applied to medical diagnosis system and will help doctors to select the effective symptoms and could make diagnosis of diseases concern. This theory also helps in selecting right political leaders.

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5

BUSTINCE, HUMBERTO, EDURNE BARRENECHEA, MIGUEL PAGOLA, et al. "GENERALIZED ATANASSOV'S INTUITIONISTIC FUZZY INDEX: CONSTRUCTION OF ATANASSOV'S FUZZY ENTROPY FROM FUZZY IMPLICATION OPERATORS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19, no. 01 (2011): 51–69. http://dx.doi.org/10.1142/s0218488511006885.

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In this paper we introduce the concept of Generalized Atanassov's Intuitionistic Fuzzy Index. We characterize it in terms of fuzzy implication operators and propose a construction method with order automorphisms. Finally, we obtain, by means of special aggregation functions applied to the generalized Atanassov's intuitionistic fuzzy index, the Atanassov's intuitionistic fuzzy entropy given by Burillo and Bustince.

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6

Shi, Xiaolong, Maryam Akhoundi, Ali Asghar Talebi, and Seyed Hossein Sadati. "Some Properties of Cubic Fuzzy Graphs with an Application." Symmetry 14, no. 12 (2022): 2623. http://dx.doi.org/10.3390/sym14122623.

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The advent of fuzzy sets, and consequently fuzzy graphs, has solved many problems in ambiguous and uncertain contexts. It is interesting and necessary to study the Wiener index in a cubic fuzzy graph that employs both fuzzy membership and interval-valued fuzzy membership at the same time. In this paper, the Wiener index in a cubic fuzzy graph is introduced as a cubic fuzzy number and some related results are described. The comparison between connectivity index and Wiener index, changes in Wiener index through deleting a node or an edge, and determining the Wiener index in some specific cubic fuzzy graphs have been the other topics studied in this research. In addition, the Wiener index is determined by mentioning concepts of the saturated cubic fuzzy cycle. In this review, the Wiener index is shown as a combination of classical and interval numbers. The results indicate that when some vertices are removed, the Wiener index may change. However, this change will not be exclusively related to both values. Finally, an application of the Wiener index is presented in the study of the properties of some monomer molecules.

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7

Wang, Gui Xiang, and Guang Tao Zhou. "Ranking Fuzzy Numbers Based on the Mean and Fuzzy Degree of Fuzzy Number." Applied Mechanics and Materials 220-223 (November 2012): 2102–8. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2102.

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In this paper, a novel approach to ranking fuzzy numbers based on the mean and the fuzzy degree of fuzzy number is proposed. In the approach, a new ranking index that is comprehensive consideration of the mean and the fuzzy degree of fuzzy number is constructed, and then the properties of the ranking index are given. Moreover, to compare the proposed approach with the existing approaches, numerical examples are given. The comparative results illustrate that the approach proposed in this paper is better and has simpler calculations.

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8

De, Sujit Kumar, and Shib Sankar Sana. "Fuzzy order quantity inventory model with fuzzy shortage quantity and fuzzy promotional index." Economic Modelling 31 (March 2013): 351–58. http://dx.doi.org/10.1016/j.econmod.2012.11.046.

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9

Wang, Zhenyuan, and Li Zhang-Westmant. "New Ranking Method For Fuzzy Numbers By Their Expansion Center." Journal of Artificial Intelligence and Soft Computing Research 4, no. 3 (2014): 181–87. http://dx.doi.org/10.1515/jaiscr-2015-0007.

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Abstract Based on the area between the curve of the membership function of a fuzzy number and the horizontal real axis, a characteristic as a new numerical index, called the expansion center, for fuzzy numbers is proposed. An intuitive and reasonable ranking method for fuzzy numbers based on this characteristic is also established. The new ranking method is applicable for decision making and data analysis in fuzz environments. An important criterion of the goodness for ranking fuzzy numbers, the geometric intuitivity, is also introduced. It guarantees coinciding with the natural ordering of the real numbers.

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10

Gil, María Angeles, Miguel López-Díaz, and Hortensia López-García. "The fuzzy hyperbolic inequality index associated with fuzzy random variables." European Journal of Operational Research 110, no. 2 (1998): 377–91. http://dx.doi.org/10.1016/s0377-2217(97)00252-x.

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