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Journal articles on the topic 'Fuzziness measure'

Author: Grafiati

Published: 4 June 2025

Last updated: 15 July 2025

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1

Lee, Sang-Hyuk, Keum-Boo Kang, and Sung shin Kim. "Measure of Fuzziness with fuzzy entropy function." Journal of Korean Institute of Intelligent Systems 14, no. 5 (2004): 642–47. http://dx.doi.org/10.5391/jkiis.2004.14.5.642.

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2

Delgado, M., M. A. Vila, and W. Voxman. "A fuzziness measure for fuzzy numbers: Applications." Fuzzy Sets and Systems 94, no. 2 (1998): 205–16. http://dx.doi.org/10.1016/s0165-0114(96)00247-3.

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3

Verma, Rohit Kumar, and M. Bhagya Laxmi. "Fuzzy Events of Theoretic Characteristics by Employing Pseudo Probabilistic Information Measure of Type Alpha." International Journal of Mathematics and Statistics Invention 13, no. 3 (2025): 24–35. https://doi.org/10.35629/4767-13032435.

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This study first examines a number of widely used fuzziness metrics for discrete fuzzy collections. We present a novel informative measure for discriminating between two fuzzy sets after examining a few of the current fuzzy set measures. We demonstrate that every class fulfills five well-known fuzziness measure axioms and show how a number of current measurements are related to these classes. The non-negative, monotony rising concave functions form the foundation of the multiplicative class. The only functions needed for the additive class are non-negative concave functions. There are also som

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4

Cardone, Barbara, and Ferdinando Di Martino. "A Novel Method Based on the Fuzzy Entropy Measure to Optimize the Fuzziness in Trapezoidal Strong Fuzzy Partitions." Information 15, no. 10 (2024): 615. http://dx.doi.org/10.3390/info15100615.

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Analyzing the uncertainty of outcomes based on estimates of the data’s membership degrees to fuzzy sets is essential for making decisions. These fuzzy sets are often designated by experts as strong fuzzy partitions of the data domain with trapezoidal fuzzy numbers. Some indices of the fuzzy set’s fuzziness provide an assessment of the degree of uncertainty of the results. It is feasible to bring the fuzzy sets’ fuzziness below a tolerable level by suitably redefining the strong fuzzy partition. Significant differences in the original fuzzy partition, however, result in disparities concerning t

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Mao, Junjun, Yuan Zhao, and Chuang Ma. "A New Type of Compositive Information Entropy for IvIFS and Its Applications." Mathematical Problems in Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/7652540.

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We first show the interval-valued intuitionistic fuzzy entropy which reflects intuitionism and fuzziness of interval-valued intuitionistic fuzzy set (IvIFS) based on interval-valued intuitionistic fuzzy cross-entropy. As for intuitionism and fuzziness of IvIFS, we propose interval-valued intuitionistic entropy and interval-valued fuzzy entropy, respectively. Furthermore, we establish the interval-valued span entropy describing the uncertainty of membership degree and nonmembership degree and show some concrete measure formulas. Combining intuitionistic factor, fuzzy factor, and span factor, we

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6

Li, Xiang, and Baoding Liu. "Chance measure for hybrid events with fuzziness and randomness." Soft Computing 13, no. 2 (2008): 105–15. http://dx.doi.org/10.1007/s00500-008-0308-x.

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7

Weiss, Brandi A., and William Dardick. "An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression." Educational and Psychological Measurement 76, no. 6 (2016): 986–1004. http://dx.doi.org/10.1177/0013164415623820.

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This article introduces an entropy-based measure of data–model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data–model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Car

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DAS, SHUBHABRATA. "ON MEASURING IMPRECISION IN HUMAN RESPONSE DUE TO RESPONDENT AND ATTRIBUTE AND ITS UTILITY IN QUESTIONNAIRE DESIGN." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 02 (2006): 155–73. http://dx.doi.org/10.1142/s0218488506003923.

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Human Response to a question with multiple alternatives can be imprecise or fuzzy for various reasons. Part of this fuzziness can be attributed to the lack of sincerity and clarity in the thought process of the respondent. A formal measure of this aspect of fuzziness is formulated in this work on the basis of consistency of the respondent's response to the same question repeated in multiple scales. Discarding haphazard and insincere respondents can improve the quality of data resulting in more efficient survey analysis. This may be achieved in the framework of statistical testing of hypothesis

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9

Han, Joon H., and Tae Y. Kim. "Ambiguity distance : an edge evaluation measure using fuzziness of edges." Fuzzy Sets and Systems 126, no. 3 (2002): 311–24. http://dx.doi.org/10.1016/s0165-0114(01)00037-9.

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10

Amato, P., and G. F. Cerofolini. "Measure, error and intrinsic fuzziness: a mathematical study of vagueness." Soft Computing 5, no. 3 (2001): 194–200. http://dx.doi.org/10.1007/s005000100081.

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11

Di Nola, A., and S. Sessa. "On the fuzziness measure and negation in totally ordered lattices." Journal of Mathematical Analysis and Applications 114, no. 1 (1986): 156–70. http://dx.doi.org/10.1016/0022-247x(86)90073-9.

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12

Dubois, Didier, Allel Hadjali, and Henri Prade. "Fuzziness and Uncertainty in Temporal Reasoning." JUCS - Journal of Universal Computer Science 9, no. (9) (2003): 1168–94. https://doi.org/10.3217/jucs-009-09-1168.

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This paper proposes a general discussion of the handling of imprecise and uncertain information in temporal reasoning in the framework of fuzzy sets and possibility theory. The introduction of fuzzy features in temporal reasoning can be related to different issues. First, it can be motivated by the need of a gradual, linguistic-like description of temporal relations even in the face of complete information. An extension of Allen relational calculus is proposed, based on fuzzy comparators expressing linguistic tolerance. Fuzzy Allen relations are defined from a fuzzy partition made by three pos

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13

Dombi, József, Jenő Fáró, and Tamás Jónás. "A Group Consensus Measure That Takes into Account the Relative Importance of the Decision-Makers." Mathematics 13, no. 3 (2025): 526. https://doi.org/10.3390/math13030526.

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In group decision making, the knowledge, skills, and experience of the decision-makers may not be at the same level. Hence, the need arises to take into account not only the opinion, but also the relative importance of the opinion of each decision-maker. These relative importance values can be treated as weights. In a group decision making situation, it is not only the weighted aggregate output that matters, but also the weighted measure of the group consensus. Noting that weighted group consensus measures have not yet been intensely studied, in this study, based on well-known requirements for

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14

Liu, Zhao Jun. "General Expression Forms on the Fuzziness Degree of Fuzzy Operator." Applied Mechanics and Materials 40-41 (November 2010): 835–38. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.835.

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In order to study fuzziness degree's quantity measure as to fuzzy operator, using fuzzy set theory, the problem of general expressions on fuzziness degree as to fuzzy operator has been studied, a series of theorems and formulas about which have been given. These formulas have a special foundation function in fuzzy information processing, such as the fuzzy pattern recognition, the fuzzy reasoning, and the fuzzy artificial intelligence. The great theory supports have been supplied to computer's fuzzy information processing.

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Xu, Yingjun. "On Uncertainty Measures of the Interval-Valued Hesitant Fuzzy Set." Advances in Fuzzy Systems 2023 (June 17, 2023): 1–11. http://dx.doi.org/10.1155/2023/3228324.

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Interval-valued hesitant fuzzy sets (IVHFS), as a kind of decision information presenting tool which is more complicated and more scientific and more elastic, have an important practical value in multiattribute decision-making. There is little research on the uncertainty of IVHFS. The existing uncertainty measure cannot distinguish different IVHFS in some contexts. In my opinion, for an IVHFS, there should exist two types of uncertainty: one is the fuzziness of an IVHFS and the other is the nonspecificity of the IVHFS. To the best of our knowledge, the existing index to measure the uncertainty

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16

Manzoor, Saima, Safina Peerzada, and Mirza A. K. Baig. "Application of Generalized Measure of ‘Useful’ R-norm Inaccuracy and Total Ambiguity." International Journal of Intelligent Systems and Applications 13, no. 1 (2021): 17–33. http://dx.doi.org/10.5815/ijisa.2021.01.02.

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In the present paper, we introduce generalized measure of 'useful' R-norm inaccuracy having two parameters and its analogue 'useful' R-norm total ambiguity measure by merging together the concepts of probability, fuzziness, R-norm, 'useful' information and inaccuracy. Along with the basic properties, some other important properties of these two proposed measures are stated. These measures are generalizations of some well-known inaccuracy measures. Further, the monotonic behaviour of the proposed 'useful' R-norm inaccuracy measures is studied and the graphical overview is given. The measure of

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17

Yang, Jie, Taihua Xu, and Fan Zhao. "Modified Uncertainty Measure of Rough Fuzzy Sets from the Perspective of Fuzzy Distance." Mathematical Problems in Engineering 2018 (August 6, 2018): 1–11. http://dx.doi.org/10.1155/2018/4160905.

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As an extension of Pawlak’s rough sets, rough fuzzy sets are proposed to deal with fuzzy target concept. As we know, the uncertainty of Pawlak’s rough sets is rooted in the objects contained in the boundary region, while the uncertainty of rough fuzzy sets comes from three regions (positive region, boundary region, and negative region). In addition, in the view of traditional uncertainty measures, the two rough approximation spaces with the same uncertainty are not necessarily equivalent, and they cannot be distinguished. In this paper, firstly, a fuzziness-based uncertainty measure is propose

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18

Maruthi, R. "Spatial Domain Method for Fusing MultiFocus Images using Measure of Fuzziness." International Journal of Computer Applications 20, no. 7 (2011): 48–51. http://dx.doi.org/10.5120/2442-3297.

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19

Cui, Wen-Hua, and Jun Ye. "Generalized Distance-Based Entropy and Dimension Root Entropy for Simplified Neutrosophic Sets." Entropy 20, no. 11 (2018): 844. http://dx.doi.org/10.3390/e20110844.

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In order to quantify the fuzziness in the simplified neutrosophic setting, this paper proposes a generalized distance-based entropy measure and a dimension root entropy measure of simplified neutrosophic sets (NSs) (containing interval-valued and single-valued NSs) and verifies their properties. Then, comparison with the existing relative interval-valued NS entropy measures through a numerical example is carried out to demonstrate the feasibility and rationality of the presented generalized distance-based entropy and dimension root entropy measures of simplified NSs. Lastly, a decision-making

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20

Maheshwari, Maheshwari, Sapna Thakur, and M. A. Siddiqui. "Generalized Parametric Fuzzy Information Measure." Indian Journal Of Science And Technology 17, no. 37 (2024): 3922–28. http://dx.doi.org/10.17485/ijst/v17i37.2527.

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Objective: To generalize an existing fuzzy information measure and verify its important properties. Methods: Both objective and descriptive methods have been adopted; problem-solving and problem-posing methods have been used. A collection of properties presented by De Luca and Termini is used as a standard for establishing new fuzzy information measures. Findings: This study has analysed the different features of the parametric measure of fuzzy information that we have presented. The suggested fuzzy entropy measure is a legitimate measure of fuzzy information since it meets all necessary requi

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21

Handa, Kenji, Prasansa Kalukottege, and Yukio Ogura. "A probabilistic interpretation of the degree of fuzziness." Journal of Applied Probability 31, no. 4 (1994): 1034–48. http://dx.doi.org/10.2307/3215327.

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In this paper we give a probabilistic interpretation for the function d(f), which has been proposed as a measure of fuzziness of a fuzzy set f. For this we construct random patterns which approximate the fuzzy set f and show that, for large n, the number of possible outcomes of the nth random pattern is approximately 2nd(f). We also give the best possible constant K in a more accurate approximation .

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22

Handa, Kenji, Prasansa Kalukottege, and Yukio Ogura. "A probabilistic interpretation of the degree of fuzziness." Journal of Applied Probability 31, no. 04 (1994): 1034–48. http://dx.doi.org/10.1017/s0021900200099551.

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In this paper we give a probabilistic interpretation for the function d(f), which has been proposed as a measure of fuzziness of a fuzzy set f. For this we construct random patterns which approximate the fuzzy set f and show that, for large n, the number of possible outcomes of the nth random pattern is approximately 2 nd(f) . We also give the best possible constant K in a more accurate approximation .

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23

Maheshwari, Thakur Sapna, and A. Siddiqui M. "Generalized Parametric Fuzzy Information Measure." Indian Journal of Science and Technology 17, no. 37 (2024): 3922–28. https://doi.org/10.17485/IJST/v17i37.2527.

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Abstract <strong>Objective</strong>: To generalize an existing fuzzy information measure and verify its important properties. <strong>Methods:</strong> Both objective and descriptive methods have been adopted; problem-solving and problem-posing methods have been used. A collection of properties presented by De Luca and Termini is used as a standard for establishing new fuzzy information measures.<strong> Findings:</strong> This study has analysed the different features of the parametric measure of fuzzy information that we have presented. The suggested fuzzy entropy measure

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24

Tiwari, Pratiksha. "Generalized Entropy and Similarity Measure for Interval-Valued Intuitionistic Fuzzy Sets With Application in Decision Making." International Journal of Fuzzy System Applications 10, no. 1 (2021): 64–93. http://dx.doi.org/10.4018/ijfsa.2021010104.

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Interval-valued intuitionistic fuzzy environment is appropriate for most of the practical scenarios involving uncertainty, vagueness, and insufficient information. Entropy, similarity, distance, inclusion, and cross entropy measures are a few methods used for measuring uncertainty and classifying fuzzy sets and its generalizations. Entropy of a fuzzy set describes fuzziness degree of the set and similarity measure measures similarity between two fuzzy or members of its extended family. This paper presents generalized entropy and similarity measures for interval-valued intuitionistic fuzzy sets

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25

N.C., Ho N. C. "Hedge Algebras: An Algebraic Approach to Domains of Linguistic Variables and Their Applicability." ASEAN Journal on Science and Technology for Development 23, no. 1&2 (2017): 1. http://dx.doi.org/10.29037/ajstd.84.

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The paper is an overview on an algebraic approach to domains of linguistic variables and somefirst applications to show the applicability of this new approach. In this approach, each linguistic domain can be considered as a hedge algebra (HA for short) and based on the structure of HAs,a notion of fuzziness measure of linguistic hedges and terms can be defined. In order to apply hedge algebras to those problems, the results of which are needed, a notion of semantically quantifying mappings (SQMs) will be introduced. It shown that there is a closed connection between SQMs and fuzziness measure

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26

Inuiguchi, Masahiro, Salvatore Greco, Roman Słowinski, and Tetsuzo Tanino. "Possibility and necessity measure specification using modifiers for decision making under fuzziness." Fuzzy Sets and Systems 137, no. 1 (2003): 151–75. http://dx.doi.org/10.1016/s0165-0114(02)00438-4.

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27

Heikkila, Eric J., Ti-Yan Shen, and Kai-Zhong Yang. "Fuzzy Urban Sets: Theory and Application to Desakota Regions in China." Environment and Planning B: Planning and Design 30, no. 2 (2003): 239–54. http://dx.doi.org/10.1068/b12820.

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This paper outlines a method for using the mathematics of fuzzy sets that is well suited to measure and characterize periurbanizing ( desakota) systems typical of China, Southeast Asia, and other areas experiencing rapid urbanization. Drawing on Kosko's ‘fuzzy hypercube’, we derive three distinct but interdependent measures: (1) extent of urbanization, (2) level of fuzziness, and (3) degree of entropy. The feasibility of the proposed method is demonstrated by using remote sensing data for Ningbo, China.

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28

LIU, Ying, Xin GUAN, and Bin WU. "Research on decision method based on probability hesitation fuzzy comprehensive distance measure." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 41, no. 6 (2023): 1209–20. http://dx.doi.org/10.1051/jnwpu/20234161209.

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Aiming at the defects of the existing probabilistic hesitation fuzzy distance measures, which require the number of membership degree to be consistent and the order to be rearranged, a probabilistic hesitation fuzzy multi-attribute decision making method based on the comprehensive characteristic distance measure is proposed. First, a new law of probability hesitant fuzzy number comparison is defined. Then four characteristics of aggregation, discreteness, fuzziness and consistency are defined, and a new comprehensive distance measure is defined based on definitions above. Finally, on the basis

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WEI, LI-LI, and WEN-XIU ZHANG. "PROBABILISTIC ROUGH SETS CHARACTERIZED BY FUZZY SETS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12, no. 01 (2004): 47–60. http://dx.doi.org/10.1142/s0218488504002643.

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Theories of fuzzy sets and rough sets have emerged as two major mathematical approaches for managing uncertainty that arises from inexact, noisy, or incomplete information. They are generalizations of classical set theory for modelling vagueness and uncertainty. Some integrations of them are expected to develop a model of uncertainty stronger than either. The present work may be considered as an attempt in this line, where we would like to study fuzziness in probabilistic rough set model, to portray probabilistic rough sets by fuzzy sets. First, we show how the concept of variable precision lo

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Wei, Cuiping, and Yuzhong Zhang. "Entropy Measures for Interval-Valued Intuitionistic Fuzzy Sets and Their Application in Group Decision-Making." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/563745.

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Entropy measure is an important topic in the fuzzy set theory and has been investigated by many researchers from different points of view. In this paper, two new entropy measures based on the cosine function are proposed for intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets. According to the features of the cosine function, the general forms of these two kinds of entropy measures are presented. Compared with the existing ones, the proposed entropy measures can overcome some shortcomings and be used to measure both fuzziness and intuitionism of these two fuzzy sets; as a r

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Ikuta, Akira, and Hisako Orimoto. "State estimation for sound environment system by using Bayesian filter based on fuzzy observation." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 2 (2023): 6311–17. http://dx.doi.org/10.3397/in_2023_0932.

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The specific signal in a sound environment is measured in decibel scale and often contains the fuzziness due to several causes. Furthermore, there exists usually a background noise in addition to the specific signal. In this study, a Bayesian filter for estimating the specific signal, based on the observed data containing the fuzziness and the effects of a background noise with non-Gaussian type, is proposed. More specifically, the energy variables satisfying the additive property of the specific signal and background noise are first considered. Next, after introducing an expansion expression

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Sharma, Sonam, and Surender Singh. "A Complementary Dual of Single-Valued Neutrosophic Entropy with Application to MAGDM." Mathematics 10, no. 20 (2022): 3726. http://dx.doi.org/10.3390/math10203726.

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A single-valued neutrosophic set (SVNS) is a subcategory of neutrosophic set that is used to represent uncertainty and fuzziness in three tiers, namely truthfulness, indeterminacy, and falsity. The measure of entropy of a SVNS plays an important role to determine the ambiguity in a variety of situations. The knowledge measure is a dual form of entropy and is helpful in certain counterintuitive situations. In this paper, we introduce a knowledge measure for the SVNS and contrast the same with existing measures. The comparative study reveals that the proposed knowledge measure is more effective

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Pu, Jiaozi, and Zongxin Liu. "Cloud Improvement Model of Niche Width and Its Application in Tram Evaluation." Wireless Communications and Mobile Computing 2022 (September 7, 2022): 1–9. http://dx.doi.org/10.1155/2022/1599664.

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Niche theory is one of the most important theories and tools in ecology. Niche width is a concept used to measure the position and role of an individual or population in a biological community. However, in the measurement of niche width, due to the unique characteristics of ecosystems, evaluators often give information based on subjective judgment to describe the status of ecological factors. Natural language is used to describe the state of ecological factors, and all the observed values come from the subjective judgment of the language value of the evaluator and have fuzziness and randomness

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34

El Santty, Mohamed Ibrahim, Hegazy Mohamed Zaher, and Naglaa Ragaa Saeid. "Organization Performance Composite Index Under Fuzziness: Application on Manufacturing Organization." Production Engineering Archives 29, no. 1 (2023): 14–22. http://dx.doi.org/10.30657/pea.2023.29.3.

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Abstract Measuring the organization’s performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include multiple dimensions. The relative importance of the multiple dimensions varies depending on the organization’s context and the management team’s visions. The vagueness and ambiguity in the management team’s perspective toward the dimensions and associated sub-indicators show fuzzy property. This paper aims to synthesize the overall organization performance in one aggregated index, engage the management team through index formulation,

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Pandey, Sakshi Dev, A. S. Ranadive, Sovan Samanta, and Biswajit Sarkar. "Bipolar-Valued Fuzzy Social Network and Centrality Measures." Discrete Dynamics in Nature and Society 2022 (June 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/9713575.

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The concept of bipolar-valued fuzzy relationships and their role in modeling bipolar-valued fuzzy social networks (BVFSN) are discussed. The goal of this study is to represent the bipolarity and fuzziness that are always present in the relationship between actors. Ranking the most central actors to achieve maximum spreading ability has been a difficult and critical topic thus far. Many centrality measures have been proposed to determine the significance of nodes in the central person detection process. In this article, we proposed two new centrality measures, BF-degree centrality and BF-closen

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Abu Qamar, Majdoleen, and Nasruddin Hassan. "Entropy, Measures of Distance and Similarity of Q-Neutrosophic Soft Sets and Some Applications." Entropy 20, no. 9 (2018): 672. http://dx.doi.org/10.3390/e20090672.

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The idea of the Q-neutrosophic soft set emerges from the neutrosophic soft set by upgrading the membership functions to a two-dimensional entity which indicate uncertainty, indeterminacy and falsity. Hence, it is able to deal with two-dimensional inconsistent, imprecise, and indeterminate information appearing in real life situations. In this study, the tools that measure the similarity, distance and the degree of fuzziness of Q-neutrosophic soft sets are presented. The definitions of distance, similarity and measures of entropy are introduced. Some formulas for Q-neutrosophic soft entropy wer

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Yager, Ronald R. "Measures of Information in Generalized Constraints." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 06, no. 06 (1998): 519–32. http://dx.doi.org/10.1142/s0218488598000409.

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The concept of a generalized constraint is introduced and as means of representing different kinds of information. The measurement of the amount of information contained in these constraints is then considered. First we consider possibilistic constraints, those in which the associated variable can take on only one value and show that the measure of specificity provides the appropriate measure. We then provide a measure of information in a fuzzy graph. We next turn to veristic constraints, those in which the associated variable can assume multiple values, and show that the associated measure of

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Menin, Boris Michailovich. "Applying Measurement Theory and Information-based Measure in Modeling Physical Phenomena and Technological Processes." European Journal of Engineering Research and Science 3, no. 1 (2018): 28. http://dx.doi.org/10.24018/ejers.2018.3.1.594.

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In this paper, we compare the features of the application of the theory of measurements and the measure of the similarity of the model to the phenomenon under study on the basis of calculating the amount of information contained in the model. An experimental estimate compared with the standard model’s uncertainty calculation procedure shows that this measure is preferable to the traditional approach to calculating the threshold discrepancy. The article presents an algorithm that is used to calculate the minimum achievable uncertainty in the resolution of the model's fuzziness, as well as exper

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Menin, Boris Michailovich. "Applying Measurement Theory and Information-based Measure in Modeling Physical Phenomena and Technological Processes." European Journal of Engineering and Technology Research 3, no. 1 (2018): 28–34. http://dx.doi.org/10.24018/ejeng.2018.3.1.594.

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In this paper, we compare the features of the application of the theory of measurements and the measure of the similarity of the model to the phenomenon under study on the basis of calculating the amount of information contained in the model. An experimental estimate compared with the standard model’s uncertainty calculation procedure shows that this measure is preferable to the traditional approach to calculating the threshold discrepancy. The article presents an algorithm that is used to calculate the minimum achievable uncertainty in the resolution of the model's fuzziness, as well as exper

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40

Garg, Harish, Nikunj Agarwal та Alka Tripathi. "Generalized Intuitionistic Fuzzy Entropy Measure of Order α and Degree β and Its Applications to Multi-Criteria Decision Making Problem". International Journal of Fuzzy System Applications 6, № 1 (2017): 86–107. http://dx.doi.org/10.4018/ijfsa.2017010105.

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The objective of this manuscript is divided into two fold. Firstly, a more generalized intuitionistic fuzzy entropy measure of order and degree has been presented for measuring the degree of fuzziness of the set with a proof of its validity. A structured linguistic variable has been taken as an illustrative example to show its validity and superiority than the existing measures. Furthermore, based on this measure, an approach to deal with multi-criteria decision making (MCDM) problem is developed. Finally, a practical example is provided to illustrate the decision making process. A computed re

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Ghosh, Swarup Kr, Biswajit Biswas, and Anupam Ghosh. "A novel Approach of Retinal Image Enhancement using PSO System and Measure of Fuzziness." Procedia Computer Science 167 (2020): 1300–1311. http://dx.doi.org/10.1016/j.procs.2020.03.446.

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Jin, Feifei, Lidan Pei, Huayou Chen, Reza Langari, and Jinpei Liu. "A Novel Decision-Making Model with Pythagorean Fuzzy Linguistic Information Measures and Its Application to a Sustainable Blockchain Product Assessment Problem." Sustainability 11, no. 20 (2019): 5630. http://dx.doi.org/10.3390/su11205630.

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This study presents a novel multi-attribute decision-making (MADM) model on the basis of Pythagorean fuzzy linguistic information measures. To do so, we first present a new concept of Pythagorean fuzzy linguistic sets to describe fuzziness and inconsistent information, in which the Pythagorean fuzzy linguistic values (PFLVs) are represented by the linguistic membership degree and linguistic non-membership degree. Then, we introduce two axiomatic definitions of information measures for PFLVs, including Pythagorean fuzzy linguistic entropy and the Pythagorean fuzzy linguistic similarity measure,

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Joshi, Vaishali Manish, and Javid Dar. "Some Results On Mathai-Haubold Fuzzy Entropy." European Journal of Pure and Applied Mathematics 17, no. 3 (2024): 2349–60. http://dx.doi.org/10.29020/nybg.ejpam.v17i3.5304.

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The concept of entropy, emerged from thermodynamics and statistical mechanics is of fundamental importance in some scientific and technological areas such as communication theory, physics, probability and statistics. Fuzzy entropy is much looked upon concept for measuring fuzzy information. The concept of fuzzy entropy was firstly mentioned by Zadeh way back in 1965 asa measure of fuzziness. In this paper , we introduce Mathai - Haubold fuzzy entropy with the proof of its validity. In addition, the elegant properties are studied of the proposed fuzzy entropy measure.

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Li, Guan Yu, Yan Zhao, and Hai Yan Li. "Imprecise Ontology Merging Framework Design." Applied Mechanics and Materials 135-136 (October 2011): 578–84. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.578.

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Precision is selected unwillingly by human being when dealing with imprecise objects because of the limitation of human cognitive ability, which deviates from the substance of the processed object when it gets the feasible way of solution. Nowadays, in terms of the research in the Ontology and the Semantic Web, the time for the transformation from the “precise phase” to the “imprecise phase” is ripe. The interoperability among ontologies is seriously blocked by the heterogeneity of ontologies constructed under distributed environment. In this case, Ontology merging in the same domain is the mo

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Tan, Chunqiao, Benjiang Ma, Desheng Dash Wu, and Xiaohong Chen. "Multi-Criteria Decision Making Methods Based on Interval-Valued Intuitionistic Fuzzy Sets." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, no. 03 (2014): 469–88. http://dx.doi.org/10.1142/s0218488514500238.

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Fuzziness is inherent in decision data and decision making process. In this paper, interval-valued intuitionistic fuzzy set is used to capture fuzziness in multi-criteria decision making problems. The purpose of this paper is to develop a new method for solving multi-criteria decision making problem in interval-valued intuitionistic fuzzy environments. First, we introduce and discuss the concept of interval-valued intuitionistic fuzzy point operators. Using the interval-valued intuitionistic fuzzy point operators, we can reduce the degree of uncertainty of the elements in a universe correspond

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Cardone, Barbara, and Ferdinando Di Martino. "A Fuzzy Entropy-Based Thematic Classification Method Aimed at Improving the Reliability of Thematic Maps in GIS Environments." Electronics 11, no. 21 (2022): 3509. http://dx.doi.org/10.3390/electronics11213509.

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Thematic maps of spatial data are constructed by using standard thematic classification methods that do not allow management of the uncertainty of classification and, consequently, evaluation of the reliability of the resulting thematic map. We propose a novel fuzzy-based thematic classification method applied to construct thematic maps in Geographical Information Systems. An initial fuzzy partition of the domain of the features of the spatial dataset is constructed using triangular fuzzy numbers; our method finds an optimal fuzzy partition evaluating the fuzziness of the fuzzy sets by using a

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Ho, Nguyen Cat, and Nguyen Van Long. "Fuzziness measure on complete hedge algebras and quantifying semantics of terms in linear hedge algebras." Fuzzy Sets and Systems 158, no. 4 (2007): 452–71. http://dx.doi.org/10.1016/j.fss.2006.10.023.

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Rashid, Tabasam, Shahzad Faizi, and Sohail Zafar. "Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making." Advances in Fuzzy Systems 2018 (July 17, 2018): 1–10. http://dx.doi.org/10.1155/2018/3637897.

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Fuzzy entropy means the measurement of fuzziness in a fuzzy set and therefore plays a vital role in solving the fuzzy multicriteria decision making (MCDM) and multicriteria group decision making (MCGDM) problems. In this study, the notion of the measure of distance based entropy for uncertain information in the context of interval-valued intuitionistic fuzzy set (IVIFS) is introduced. The arithmetic and geometric average operators are firstly used to aggregate the interval-valued intuitionistic fuzzy information provided by the decision makers (DMs) or experts corresponding to each alternative

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Nagalakshmi, T., and G. Uthra. "A New Approach to Find an Optimal Solution of a Fuzzy Linear Programming Problem by Fuzzy Dynamic Programming." International Journal of Engineering & Technology 7, no. 4.10 (2018): 360. http://dx.doi.org/10.14419/ijet.v7i4.10.20935.

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This paper mainly focuses on a new approach to find an optimal solution of a fuzzy linear programming problem with the help of Fuzzy Dynamic Programming. Linear programming deals with the optimization of a function of variables called an objective function, subject to a set of linear inequalities called constraints. The objective function may be maximizing the profit or minimizing the cost or any other measure of effectiveness subject to constraints imposed by supply, demand, storage capacity, etc., Moreover, it is known that fuzziness prevails in all fields. Hence, a general linear programmin

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Maruthi, R., and C. JayaKumari. "Fusion Scheme for fusing images with diverse focuses using index of fuzziness as a focus measure." Procedia Engineering 30 (2012): 584–90. http://dx.doi.org/10.1016/j.proeng.2012.01.902.

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