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Thematische Bibliographien / Fuzzy sets (FS)

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Auswahl der wissenschaftlichen Literatur zum Thema „Fuzzy sets (FS)“

Autor: Grafiati

Veröffentlicht am 2. Juni 2025

Zuletzt aktualisiert am 31. Juli 2025

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Zeitschriftenartikel zum Thema "Fuzzy sets (FS)"

1

Farhadinia, Bahram, and Francisco Chiclana. "Extended Fuzzy Sets and Their Applications." Mathematics 9, no. 7 (2021): 770. http://dx.doi.org/10.3390/math9070770.

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This contribution deals with introducing the innovative concept of extended fuzzy set (E-FS), in which the S-norm function of membership and non-membership grades is less than or equal to one. The proposed concept not only encompasses the concept of the fuzzy set (FS), but it also includes the concepts of the intuitionistic fuzzy set (IFS), the Pythagorean fuzzy set (PFS) and the p-rung orthopair fuzzy set (p-ROFS). In order to explore the features of the E-FS concept, set and algebraic operations on E-FSs, average and geometric operations of E-FSs are studied and an E-FS score function is def

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Liu, Xiaoting, Huang Shan, and Kefeng Li. "Triangular Norm based Invex Fuzzy Sets." Advances in Engineering Technology Research 1, no. 1 (2022): 198. http://dx.doi.org/10.56028/aetr.1.1.198.

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Zadeh’s convex fuzzy set (CFS for short) have two important properties, (1) fuzzy set (FS for short) is convex iff its cuts are convex, (2) arbitrary intersection of CFSs is a CFS. Generalized CFS, named-invex FS is introduced. Meanwhile, two properties above are generalized into-invex FS.

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Abuhijleh, Eman A., Mourad Massa’deh, Amani Sheimat, and Abdulazeez Alkouri. "Complex Fuzzy Groups Based on Rosenfeld’s Approach." WSEAS TRANSACTIONS ON MATHEMATICS 20 (August 4, 2021): 368–77. http://dx.doi.org/10.37394/23206.2021.20.38.

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Complex fuzzy sets (CFS) generalize traditional fuzzy sets (FS) since the membership functions of CFS reduces to the membership functions of FS. FS values are always at [0, 1], unlike CFS which has values in the unit disk of C. This paper merges notion and concept in group theory and presents the notion of a complex fuzzy subgroup of a group. This proposed idea represents a more general and better optional mathematical tool as one of the approaches in the fuzzy group. However, this research defines the notion of complex fuzzy subgroupiod, complex fuzzy normal subgroup, and complex fuzzy left(r

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Chaudhary, Gopal, Amena .., and J. A. Lobo Marques. "Sentiment Analysis from Social Media Tweets Using Single-Valued Neutrosophic Sets and Fuzzy Sets." Journal of Neutrosophic and Fuzzy Systems 5, no. 2 (2023): 51–59. http://dx.doi.org/10.54216/jnfs.050205.

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In the last ten years, exciting work at the intersection of several academic disciplines has been done in the areas of view mining and sentiment analysis. The sheer amount of social media text that is now accessible for sentiment analysis has expanded by a factor of multiples with the development of social media networks, resulting in the creation of a formidable corpus. An examination of the sentiments included within tweets has been performed to measure the general public's perspective on breaking news, as well as a variety of laws, regulations, individuals, and political movements. In the a

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Liu, Sicong, and Rui Cai. "Uncertainty of Interval Type-2 Fuzzy Sets Based on Fuzzy Belief Entropy." Entropy 23, no. 10 (2021): 1265. http://dx.doi.org/10.3390/e23101265.

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Interval type-2 fuzzy sets (IT2 FS) play an important part in dealing with uncertain applications. However, how to measure the uncertainty of IT2 FS is still an open issue. The specific objective of this study is to present a new entropy named fuzzy belief entropy to solve the problem based on the relation among IT2 FS, belief structure, and Z-valuations. The interval of membership function can be transformed to interval BPA [Bel,Pl]. Then, Bel and Pl are put into the proposed entropy to calculate the uncertainty from the three aspects of fuzziness, discord, and nonspecificity, respectively, w

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Dai, Songsong. "Quaternionic Fuzzy Sets." Axioms 12, no. 5 (2023): 490. http://dx.doi.org/10.3390/axioms12050490.

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A novel concept of quaternionic fuzzy sets (QFSs) is presented in this paper. QFSs are a generalization of traditional fuzzy sets and complex fuzzy sets based on quaternions. The novelty of QFSs is that the range of the membership function is the set of quaternions with modulus less than or equal to one, of which the real and quaternionic imaginary parts can be used for four different features. A discussion is made on the intuitive interpretation of quaternion-valued membership grades and the possible applications of QFSs. Several operations, including quaternionic fuzzy complement, union, int

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Ayub, Saba, Muhammad Shabir, Muhammad Riaz, Faruk Karaaslan, Dragan Marinkovic, and Djordje Vranjes. "Linear Diophantine Fuzzy Rough Sets on Paired Universes with Multi Stage Decision Analysis." Axioms 11, no. 12 (2022): 686. http://dx.doi.org/10.3390/axioms11120686.

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Rough set (RS) and fuzzy set (FS) theories were developed to account for ambiguity in the data processing. The most persuasive and modernist abstraction of an FS is the linear Diophantine FS (LD-FS). This paper introduces a resilient hybrid linear Diophantine fuzzy RS model (LDF-RS) on paired universes based on a linear Diophantine fuzzy relation (LDF-R). This is a typical method of fuzzy RS (F-RS) and bipolar FRS (BF-RS) on two universes that are more appropriate and customizable. By using an LDF-level cut relation, the notions of lower approximation (L-A) and upper approximation (U-A) are de

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Al-shami, Tareq M., Salem Saleh, Alaa M. Abd El-latif, and Abdelwaheb Mhemdi. "Novel categories of spaces in the frame of fuzzy soft topologies." AIMS Mathematics 9, no. 3 (2024): 6305–20. http://dx.doi.org/10.3934/math.2024307.

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<abstract><p>In the present paper, we introduce and discuss a new set of separation properties in fuzzy soft topological spaces called $ FS\delta $-separation and $ FS\delta $-regularity axioms by using fuzzy soft $ \delta $-open sets and the quasi-coincident relation. We provide a comprehensive study of their properties with some supporting examples. Our analysis includes more characterizations, results, and theorems related to these notions, which contributes to a deeper understanding of fuzzy soft separability properties. We show that the $ FS\delta $-separation and $ FS\delta $

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Zhang, Zhen Hua, Yong Hu, and Xiao Hua Ke. "A Dynamic Fuzzy Sets Method and its Application to Pattern Recognition." Applied Mechanics and Materials 263-266 (December 2012): 2602–5. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2602.

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We present a novel dynamic fuzzy sets (DFS) method, which is the generalization of fuzzy sets (FS) and the dynamization of interval-valued intuitionistic fuzzy sets (IVIFS). First, by analyzing the degree of hesitancy, we propose a DFS model from IVIFS. Second, we introduce the distance measure of DFS. Finally, a pattern recognition example is given to demonstrate the application of DFS, and the experimental results show that the DFS method is more effective than some IVIFS methods.

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HEIDARZADE, ARMAGHAN, NEZAM MAHDAVI-AMIRI, and IRAJ MAHDAVI. "A NEW DISTANCE FOR INTERVAL TYPE-2 FUZZY SETS WITH AN APPLICATION TO CLUSTERING." International Journal of Computational Intelligence and Applications 13, no. 04 (2014): 1450020. http://dx.doi.org/10.1142/s1469026814500205.

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Type-2 fuzzy sets are generalizations of ordinary fuzzy sets, in which membership grades are characterized by fuzzy membership functions. Here, a problem of finding distance between two interval type-2 fuzzy sets (IT2-FSs) was considered. Based on a new definition of centroid for an IT2-FS, a formulation for calculation of the distance between two IT2-FSs was introduced, and an algorithm was explained to obtain it. The proposed distance formula was incorporated in Yang and Shih's clustering algorithm to reach a clustering method for interval type-2 fuzzy data sets. The applicability of the pro

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Bücher zum Thema "Fuzzy sets (FS)"

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Schneider, Carsten Q. Improving inference with a "two-step" approach: Theory and limited diversity in fs/QCA. European University Institute, 2003.

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Buchteile zum Thema "Fuzzy sets (FS)"

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Abdullah Lazim and Kamal C.W. Rabiatul Adawiyah C.W. "A New Integrating SAW-TOPSIS Based on Interval Type-2 Fuzzy Sets for Decision Making." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-722-1-45.

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Most of the integrated methods of multi-attributes decision making (MADM) used type-1 fuzzy sets to represent uncertainties. Recent theory has suggested that interval type-2 fuzzy sets (IT2 FS) could be used to enhance representation of uncertainties in decision making problems. Differently from the typical integrated MADM methods which directly used type-1 fuzzy sets, this paper proposes an integrating simple additive weighting &ndash; technique for order preference similar to ideal solution (SAW-TOPSIS) based on IT2 FS to enhance judgment. The SAW with IT2 FS is used to determine the wei

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Mukherjee, Saikat, Wayenbam Sobhachandra Singh, and Sumita Banerjee. "Computational and Theoretical Techniques in Biomedicine." In Frontiers in Nanomedicine. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815136920123030011.

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Biomedicine research has gained momentum for the development of various computational and theoretical techniques. Researchers working in biomedicine and bioinformatics depend on computational intelligence and its widespread applications. New algorithms have been described that enable computational simulations and mathematical modelling in coordination with analytical methods to comprehensively study biological systems. Many algorithms, such as Artificial Neural Networks (ANNs), Rough Sets (RS), Fuzzy Sets (FS), Particle Swarm Optimization (PSO), Evolutionary Algorithm (EA), etc., allow reliabl

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Mishra, Sushruta, Soumya Sahoo, and Brojo Kishore Mishra. "Neuro-Fuzzy Models and Applications." In Emerging Trends and Applications in Cognitive Computing. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5793-7.ch004.

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The modern techniques of artificial intelligence have found application in almost all the fields of human knowledge. Among them, two important techniques of artificial intelligence, fuzzy systems (FS) and artificial neural networks (ANNs), have found many applications in various fields such as production, control systems, diagnostic, supervision, etc. They evolved and improved throughout the years to adapt arising needs and technological advancements. However, a great emphasis is given in the engineering field. The techniques of artificial intelligence based on fuzzy logic and neural networks

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Konferenzberichte zum Thema "Fuzzy sets (FS)"

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Santos, Gabriel Marcondes, Emmanuel Tavares Ferreira Affonso, Alisson Marques Silva, and Gray Farias Moita. "Fuzzy C-Means com Método Wrapper Com Baixo Custo Computacional de Seleção de Atributos." In Congresso Brasileiro de Inteligência Computacional. SBIC, 2021. http://dx.doi.org/10.21528/cbic2021-87.

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Nowadays the Computational Intelligence (IC) algorithms have shown a lot of efficiency in pattern classification and recognition processes. However, some databases may contain irrelevant attributes that may be detrimental to the learning of the classification model. In order to detect and exclude input attributes with little representativeness in the data sets presented to the classification algorithms, the Features Selection (FS) methods are commonly used. The goal of features selection methods is to minimize the number of input attributes processed by a classifier in order to improve its ass

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