A novel clustering algorithm based on a new similarity measure over Intuitionistic fuzzy sets

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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“…If d is the distance measure between intuitionistic fuzzy sets (IFSs) [23], the following attributes should be satisfied:…”

Section: Intuitionistic Fuzzy Clustering Algorithm (Ifcm) a Fuzzmentioning

confidence: 99%

“…Since the value of η ik depends on u jk , the derivation method in [23] cannot be used when calculating the derivative for u jk . And in the objective function of [29], there may be a case of missing parentheses, which leads to different problems.…”

Section: Improved Ifcm Form Based On Distribution Informationmentioning

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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“…The fuzzy variants of GRA are proposed (see: [38], [39], [40]) to deal with the imprecise information. AIFS is an application-rich and highly studied extension of the fuzzy set (see: [41], [42], [43]). In literature, we come across the proposals of AIFS-based variants of GRA (see: [44], [45], [46]).…”

Section: Introductionmentioning

confidence: 99%

Proposed Intuitionistic Fuzzy Entropy Measure Along With Novel Multicriteria Sorting Techniques

Tiwari

Lohani

2023

IEEE Access

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Recently, the major environmental changes and a pandemic called COVID-19 have heavily impacted the economy, business, and health of each country. Moreover, the climatic changes and COVID-19 are calamities to human life. In other words, these two aspects threaten the existence of humans and the sustenance of the all-around development of a country. These two factors particularly influence the tourism sector, so a strategy balancing environmental quality and dealing with the ill effects of COVID-19 is formulated to uplift the economic sectors. Atannasov's intuitionistic fuzzy domain is used to model the environmental quality and COVID-19 due to the involvement of hesitancy and uncertainty. The precise measurement of the imprecision in the information is obtained with the help of entropy measure. The paper analyzes the two aspects using a novel entropy measure based on multiple criteria sorting (MCS). Here, the two MCS problems are solved with the help of two proposed techniques: TOPSIS-GREY-sort and ENTROPY-TOPSIS-GREY-sort. A case study showing the impact of COVID-19 in the Philippines and the environmental quality of Tehran (the capital city of Iran) are considered to validate the functioning of the proposed techniques. We use "A novel sorting method TOPSIS-SORT: an application for Tehran environmental quality evaluation (2016), Ekonomica a management", and "Current Issues in Tourism 25.2(2022): 168-178, Taylor and Francis" for the comparative analysis.INDEX TERMS Atanassov intuitionistic fuzzy set (AIFS), Multi critria sorting (MCS), Entropy, COVID-19, Environmental quality, TOPSIS, GRA.

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“…In literature, various distance measures were used to introduce different variants of clustering algorithm. One of the most commonly uses measure is l p − metric (see [43], [44], [45], [46] ). A spherical or ball-shaped geometry is formed around the clusters when Euclidean distance measure is used.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2022

JIASF

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In machine learning, distance measure plays an important role in defining the similarity between two data-items. In the paper, we discuss some of the drawbacks of distance measures (metrics) with their possibly induced clustering algorithms. Further, to overcome the drawbacks, we propose a novel intuitionistic fuzzy distance measure associated with generalized cesáro paranormed sequence space Ces q p (F ). We also discuss some geometric properties of Ces q p (F ). Moreover, the proposed distance measure is utilized in k-mean clustering algorithm to propose fuzzy c-mean clustering algorithm for Ces q p (F ).

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A novel clustering algorithm based on a new similarity measure over Intuitionistic fuzzy sets

Cited by 20 publications

References 28 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

Proposed Intuitionistic Fuzzy Entropy Measure Along With Novel Multicriteria Sorting Techniques

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