The advanced defuzzification methods of the convex α – cut fuzzy sets [PDF]
E3S Web of Conferences, 2023 The main features of the fuzzy sets and their corresponding membership functions were presented in terms of the fuzzification process and further by the de-fuzzification operation.
Gadjiev Djavanshir +2 more
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Almost bi-hyperideals and their fuzzification of semihypergroups
Journal of Mathematics and Computer Science, 2021 In this paper, we introduce the concept of almost bi-hyperideals of semihypergroups which is a generalization of bi-hyperideals, and we give some properties of them.
Patcharee Muangdoo +2 more
semanticscholar +1 more source
Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation [PDF]
International Journal of Advanced Computer Science and Applications, 2020 Big Data is used by data miner for analysis purpose which may contain sensitive information. During the procedures it raises certain privacy challenges for researchers.
S. Khan +5 more
semanticscholar +1 more source
A Dimension Reduction Framework for HSI Classification Using Fuzzy and Kernel NFLE Transformation
Remote Sensing, 2015 In this paper, a general nearest feature line (NFL) embedding (NFLE) transformation called fuzzy-kernel NFLE (FKNFLE) is proposed for hyperspectral image (HSI) classification in which kernelization and fuzzification are simultaneously considered.
Ying-Nong Chen +4 more
doaj +1 more source
Constructing a Precise Fuzzy Feedforward Neural Network Using an Independent Fuzzification Approach
Axioms, 2021 This study discusses how to fuzzify a feedforward neural network (FNN) to generate a fuzzy forecast that contains the actual value, while minimizing the average range of fuzzy forecasts.
Hsin-Chieh Wu, T. Chen, Min-Chi Chiu
semanticscholar +1 more source
Augmentation of the Reconstruction Performance of Fuzzy C-Means with an Optimized Fuzzification Factor Vector [PDF]
Knowledge-Based Systems, 2020 Information granules have been considered to be the fundamental constructs of Granular Computing (GrC). As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one of the most frequently used methods to construct information granules. The FCM-
Kai-Jie Xu, W. Pedrycz, Zhi-Wu Li
semanticscholar +1 more source
Remote Sensing, 2017 Andrews first proposed an equation to visualize the structures within data in 1972. Since then, this equation has been used for data transformation and visualization in a wide variety of fields.
Sornkitja Boonprong +3 more
doaj +1 more source
Triangular Fuzzy-Rough Set Based Fuzzification of Fuzzy Rule-Based Systems
Journal of Artificial Intelligence and Soft Computing Research, 2020 In real-world approximation problems, precise input data are economically expensive. Therefore, fuzzy methods devoted to uncertain data are in the focus of current research.
Janusz T. Starczewski +2 more
semanticscholar +1 more source
Intersection-Based Routing with Fuzzy Multi-Factor Decision for VANETs
Applied Sciences, 2021 Due to the limitations of the urban environment, the data transferred between vehicles can only change direction at the intersections. Therefore, the routing decision at an intersection will largely affect the overall routing decision.
Zhenbo Cao, Zujie Fan, Jaesool Kim
doaj +1 more source
The Ski Climate Index (SCI): fuzzification and a regional climate modeling application for Turkey
International journal of biometeorology, 2020 Climatology has increasingly become an important discipline for understanding tourism and recreation, especially in the era of contemporary climate change.
O. Demiroglu +3 more
semanticscholar +1 more source