Clustering the intuitionistic fuzzy data: Detection of an unknown number of intuitionistic fuzzy clusters in the allotment

Shyrai, Stanislau; Viattchenin, Dmitri A.

doi:10.1109/dt.2015.7222990

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…γ is a parameter that controls the range of distance to the target center. The denominator of W jk uses a Gaussian model, indicating that the closer the pixel is to the centroid, the more likely it is to belong to the target [33]. When the pixel is at the centroid position, the probability intensity curve peaks, as shown in Figure 2.…”

Section: A Improvement Of Global Distribution Information Based On Gmentioning

confidence: 99%

An Intuitionistic Kernel-Based Fuzzy C-Means Clustering Algorithm With Local Information for Power Equipment Image Segmentation

Chen

Wang

2020

IEEE Access

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With the transformation of the national energy and power sector, the steady advancement of intelligent power grid construction and the continuous improvement of the Ubiquitous Power Internet of Things technology framework, it has further requirements for realizing state comprehensive awareness and efficient processing of information data, and has been widely used in power equipment. The infrared image recognition technology, which has been widely used in thermal fault diagnosis of power equipment, also requires deeper research. For traditional Intuitionistic Fuzzy C-means (IFCM) algorithm for image segmentation is sensitive to the clustering center lead to low final clustering precision and detail, the time complexity and the high shortage. The paper puts forward a kind of applicable to power equipment of the infrared image segmentation based on space distribution information of Intuitionistic Fuzzy clustering algorithm. Non-target objects with high intensity and uneven image intensity in infrared image have strong interference to image segmentation. The proposed algorithm can effectively suppress the interference. Firstly, the gaussian model is introduced into the global spatial distribution information of power equipment to improve the IFCM. Secondly, the spatial operator optimization membership function of local spatial information is used to solve the problem of edge blurring and uneven image intensity. Through experiments on the data set containing 300 infrared images of power equipment, the relative regional error rate is about 10%, which is less affected by the change of fuzzy factor m. The effectiveness and applicability of this algorithm are verified, which is obviously better than other comparison algorithms. INDEX TERMS Intuitionistic fuzzy clustering, infrared image, Gaussian model, local information.

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Section: A Improvement Of Global Distribution Information Based On Gmentioning

confidence: 99%

An Intuitionistic Kernel-Based Fuzzy C-Means Clustering Algorithm With Local Information for Power Equipment Image Segmentation

Chen

Wang

2020

IEEE Access

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“…An intuitionistic fuzzy tolerance relation matrix is a matrix of the initial data for the relational algorithms and a matrix of attributes is a matrix of the initial data for the prototype-based algorithms. In particular, the group of direct relational heuristic α β -clusters [12].…”

Section: Introductionmentioning

confidence: 99%

Distances and Similarity Measures in Heuristic Possibilistic Clustering the Intuitionistic Fuzzy Data: A Comparative Study

Viattchenin¹

2017

IJSMIT

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Abstract:The note deals with the problem of heuristic possibilistic clustering the intuitionistic fuzzy data. Different distances between intuitionistic fuzzy sets are considered in the paper. Similarity measures for intuitionistic fuzzy sets for constructing intuitionistic fuzzy tolerance relations are also considered. A numerical example of application of these distances and similarity measures for clustering the intuitionistic fuzzy data is presented. Some preliminary conclusions are formulated.

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A New Heuristic Algorithm of Possibilistic Clustering Based on Intuitionistic Fuzzy Relations

Kacprzyk

Owsiński

Viattchenin

et al. 2015

Advances in Intelligent Systems and Computing

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Clustering the intuitionistic fuzzy data: Detection of an unknown number of intuitionistic fuzzy clusters in the allotment

Cited by 4 publications

References 7 publications

An Intuitionistic Kernel-Based Fuzzy C-Means Clustering Algorithm With Local Information for Power Equipment Image Segmentation

An Intuitionistic Kernel-Based Fuzzy C-Means Clustering Algorithm With Local Information for Power Equipment Image Segmentation

Distances and Similarity Measures in Heuristic Possibilistic Clustering the Intuitionistic Fuzzy Data: A Comparative Study

A New Heuristic Algorithm of Possibilistic Clustering Based on Intuitionistic Fuzzy Relations

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