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Fuzzy K-means clustering with reconstructed information
Clustering techniques play a pivotal role in unveiling the inherent structure of unlabeled data. When dealing with overlap** clusters, traditional...
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Automation in Bayesian operational modal analysis using clustering-based interpretation of stabilization diagram
Long-term structural health monitoring (SHM) requires processing a large amount of data with human intervention often involved. Operational modal...
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A survey on deep clustering: from the prior perspective
Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional...
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Deep generative clustering methods based on disentangled representations and augmented data
This paper presents a novel clustering approach that utilizes variational autoencoders (VAEs) with disentangled representations, enhancing the...
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Adaptive local neighborhood information based efficient fuzzy clustering approach
The purpose of clustering is to partition data similar with each other into a same group and partition data dissimilar with each other into different...
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A dynamic core evolutionary clustering algorithm based on saturated memory
Because the number of clustering cores needs to be set before implementing the K-means algorithm, this type of algorithm often fails in applications...
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Analysis of Clustering Algorithms for Facility Location Allocation Problems
Problems with facility location include selecting where to site a facility in order to meet the specified constraints most effectively. Choosing a...
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Clustering Analysis for Newsgroup Classification
There is humongous amount of data on the internet. One such category of data is the text-based newsgroup documents that can be clustered based on...
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Nucleus Segmentation Using K-Means Clustering for Analysis of Microscopy Images
Analysis of microscopy images involves scanning of information related to color and texture. The color levels of nucleus and its neighbors especially...
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Clustering-based gradual pattern mining
Generally, the classical problem of gradual pattern mining involves generating pattern candidates and determining the number of concordant object...
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A hybrid similarity measure-based clustering approach for mixed attribute data
In mixed attribute clustering, the similarity measure superposition is skewed due to the difference of measuring different attribute types. In this...
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Unraveling Magnesium Alloy Corrosion Patterns Through Unsupervised Machine Learning: Exploring Clustering Techniques for Enhanced Insight
This research investigates the interpretation of corrosion patterns using unsupervised machine learning techniques. The use of machine learning...
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Droplet arrival pattern, clustering and settling velocity in a polydisperse droplet field
Understanding the onset of clustering is an essential consideration in many engineering and natural systems. High operating costs and sophisticated...
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Weighted Intuitionistic Fuzzy C-Means Clustering Algorithms
Atanassov intuitionistic fuzzy set (AIFS)-based C -means algorithms are successful in clustering uncertain or vague real-world datasets. The...
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Review on Teacher's Classroom Language Behavior Analysis Based on Clustering and Emotional Analysis
With the rapid development of deep learning technology, its applications in various fields are also increasing. In addition to making gratifying...
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Subspace clustering based on a multichannel attention mechanism
Existing self-representation models based on multilayer perceptrons (MLPs) have gained widespread attention for their outstanding clustering...
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Knowledge-aware progressive clustering for social image
Social image data refer to the annotated image with tags in social media, in which the tags are always labeled by users. Integrating the visual and...
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Design of Tourism Data Clustering Analysis Model Based on K-Means Clustering Algorithm
In recent years, with the development of society, tourism has become one of the most influential and largest industries in global economic growth....
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Visual navigation method for agricultural mobile robots based on spatial continuity clustering algorithm
With the development of the information age, more intelligent products have brought convenience to human life. Robots, as intelligent crystallization...
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Stochastic Disturbance Propagation Model Analysis of Power Grids Based on Epidemic Model and Improved Clustering
Based on epidemic model, a stochastic disturbance propagation model of power grids is proposed in this paper. Firstly, compared with epidemic model,...