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Electrofacies Estimation of Carbonate Reservoir in the Scotian Offshore Basin, Canada Using the Multi-resolution Graph-Based Clustering (MRGC) to Develop the Rock Property Models
Rock properties in geomechanical models depend on electrofacies. Electrofacies classification is a crucial task for generating accurate rock property...
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Block diagonal representation learning with local invariance for face clustering
Facial data under non-rigid deformation are often assumed lying on a highly non-linear manifold. The conventional subspace clustering methods, such...
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Clustering
The task of grou** data points or instances into clusters is quite fundamental in data science. In general, clustering methods belong to the area...
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Genetic Clustering-Based Equivalent Model of Wind Farm with Doubly Fed Induction Generator
With increasing the number of wind power generators, the consumption time of electromagnetic simulation of the wind farm explodes. To reduce the...
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An adaptive weighted self-representation method for incomplete multi-view clustering
For multi-view data in reality, part of its elements may be missing because of human or machine error. Incomplete multi-view clustering (IMC)...
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Quantum density peak clustering
Clustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations...
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A method for clustering rock discontinuities with multiple properties based on an improved netting algorithm
Clustering analysis is fundamental for determining dominant discontinuity properties in rock engineering. Orientation has commonly been considered...
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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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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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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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Auto-weighted multiple kernel tensor clustering
Multiple kernel subspace clustering (MKSC) has attracted intensive attention since its powerful capability of exploring consensus information by...
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Consistent multi-view subspace clustering with local structure information
Multi-view subspace clustering has attracted extensive attention in recent years because it can fully utilize the inherent characteristics of each...
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Optimizing Environment-aware VANET Clustering using Machine Learning
Clustering is important to improve the quality of service in many VANET protocols and applications, such as data dissemination, media access control,...
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Anchor-based sparse subspace incomplete multi-view clustering
In recent decades, multi-view clustering has received a lot of attention. The majority of previous research has assumed that all instances have...
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INCM: neutrosophic c-means clustering algorithm for interval-valued data
Data clustering has emerged as a prospective technique for analyzing interval-valued data and has found extensive applications across various...
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Towards intelligent user clustering techniques for non-orthogonal multiple access: a survey
With the increasing user density of wireless networks, various user partitioning techniques or algorithms segregate users into smaller, more...
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A multiple kinds of information extraction method for multi-view low-rank subspace clustering
Recently, multi-view subspace clustering has attracted intensive attentions due to the remarkable clustering performance by extracting abundant...
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An Efficient Gateway Node Selection Method for Clustering in Heterogeneous Mobile Ad-hoc Networks
Node heterogeneity such as different transmission range, battery backup and mobility lead to several issues for the network. To concentrate on these...
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Model-based clustering of multipath propagation in powerline communication channels
Powerline communication (PLC) channels are known to exhibit multipath propagation behaviour. The authors present a model-based framework to address...
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A parallel ADMM-based convex clustering method
Convex clustering has received recently an increased interest as a valuable method for unsupervised learning. Unlike conventional clustering methods...
