Results 11 to 20 of about 1,141,336 (343)
Fuzzy regression model using fuzzy partition
Journal of Physics: Conference Series, 2019 In this paper, we introduce a novel method to estimate fuzzy regression model when the center and spread have different pattern. We combine the least absolute deviations estimation for the center with discriminant analysis for spread.
Hye-Young Jung +2 more
openaire +2 more sources
Partition Coefficient and Partition Entropy in Fuzzy C Means Clustering
Journal of Scientific Research and Reports, 2023 This paper offers a comprehensive exploration of partition validation functions, specifically focusing on partition coefficient and partition entropy within the realm of fuzzy clustering—an influential approach in the field of clustering datasets.
Rohit Kumar Verma +2 more
semanticscholar +1 more source
Conditional semi‐fuzzy c‐means clustering for imbalanced dataset
IET Image Processing, 2020 Fuzzy c‐means algorithms have been widely utilised in several areas such as image segmentation, pattern recognition and data mining. However, the related studies showed the limitations in facing imbalanced datasets. The maximum fuzzy boundary tends to be
Yunlong Gao +4 more
doaj +1 more source
A Definition for Hesitant fuzzy Partitions
International Journal of Computational Intelligence Systems, 2016 In this paper, we define hesitant fuzzy partitions (H-fuzzy partitions) to consider the results of standard fuzzy clustering family (e.g. fuzzy c-means and intuitionistic fuzzy c-means).
Laya Aliahmadipour +3 more
doaj +1 more source
Molecules, 2020 Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data.
Ioana Feher +4 more
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Average-Based Fuzzy Time Series Markov Chain Based on Frequency Density Partitioning
Journal of Applied Mathematics, 2023 Fuzzy time series (FTS) is one of the forecasting methods that has been developed until now. The fuzzy time series is a forecasting method that uses the concept of fuzzy logic, which Song and Chissom first introduced.
Susilo Hariyanto +3 more
doaj +1 more source
Mathematics, 2019 We introduce the concepts of a bipolar fuzzy reflexive, symmetric, and transitive relation. We study bipolar fuzzy analogues of many results concerning relationships between ordinary reflexive, symmetric, and transitive relations.
Jeong-Gon Lee, Kul Hur
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Triangular Fuzzy Time Series for Two Factors High-order based on Interval Variations
JTAM (Jurnal Teori dan Aplikasi Matematika), 2022 Fuzzy time series (FTS) firstly introduced by Song and Chissom has been developed to forecast such as enrollment data, stock index, air pollution, etc. In forecasting FTS data several authors define universe of discourse using coefficient values with any
A. Nafis Haikal +4 more
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Possibilistic and fuzzy clustering methods for robust analysis of non-precise data [PDF]
, 2017 This work focuses on robust clustering of data affected by imprecision. The imprecision is managed in terms of fuzzy sets. The clustering process is based on the fuzzy and possibilistic approaches.
Ferraro, MARIA BRIGIDA, Giordani, Paolo
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A Modular Programmable CMOS Analog Fuzzy Controller Chip [PDF]
, 1999 We present a highly modular fuzzy inference analog CMOS chip architecture with on-chip digital programmability. This chip consists of the interconnection of parameterized instances of two different kind of blocks, namely label blocks and rule blocks. The
Delgado Restituto, Manuel +3 more
core +5 more sources