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Recidivism early warning model based on rough sets and the improved K-prototype clustering algorithm and a back propagation neural network
The rate of recidivism by criminals after their release from prison is high, which is harmful to society. Thus, it is socially significant to reduce...
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An Adaptable Algorithm for Optimizing Bus Line Distribution Using the Clustering Method
The current fleet of cars requires reevaluation, upgrades, and replacement in response to the expanding human population, the increase in urban...
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Consensus latent incomplete multi-view clustering with low-rank tensor constraint
Traditional multi-view clustering (MVC) assumes that all views are complete and it cannot address a lack of views. In real life, a lack of views...
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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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A New Generalized Pole Clustering-Based Model Reduction Technique and Its Application for Design of Controllers
A new model diminution technique is proposed for the reduction of complexity of higher order linear dynamical systems. In this proposed method, a...
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Design of students’ learning state evaluation model in online education based on double improved neural network
In today's highly developed era of information technology, online education is gradually becoming an important teaching mode. Online education...
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Sampling-based fuzzy speech clustering systems for faster communication with virtual robotics toward social applications
For social applications, virtual robotics technologies require the Internet of Things (IoT) and cloud services. IoT based-speaker identification is...
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Virtual clustering analysis for phase field model of quasi-static brittle fracture
In this paper, we develop a Virtual Clustering Analysis method for a phase field model of brittle fracture. In addition to the strain/stress field,...
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Financial Management Early Warning Model Based on Clustering Algorithm
The establishment of a scientific, reasonable and effective early warning (EW) system is of great significance to improving the efficiency of my...
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learning anomalous human actions using frames of interest and decoderless deep embedded clustering
Inconsistent data and unclear labels make it difficult to learn anomalous behavior from video. Therefore, methods based on deep clustering are now...
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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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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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Cloud model-clustering analysis based evaluation for ventilation system of underground metal mine in alpine region
Ventilation system is significant in underground metal mine of alpine region. Reasonable evaluation of ventilation effectiveness will lead to a...
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Multi-label feature selection via spectral clustering-based label enhancement and manifold distribution consistency
Multi-label feature selection can effectively improve the performance and efficiency of subsequent learning tasks by selecting important features...
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Automatic Landslide Segmentation Using a Combination of Grad-CAM Visualization and K-Means Clustering Techniques
Rapid detection and accurate map** of landslides are crucial for damage detection and subsequent prevention of secondary damage. In this study, a...
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Investigating the influence of clustering techniques and parameters on a hybrid PSO-driven ANFIS model for electricity prediction
The availability of reliable electrical power, which is essential for a comfortable lifestyle worldwide, requires realistic power usage projections...
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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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Time series clustering of dynamical systems via deterministic learning
A recent deterministic learning theory has achieved locally-accurate identification of unknown system dynamics. This article presents a novel...
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Clustering method for time-series images using quantum-inspired digital annealer technology
Time-series clustering is a powerful data mining technique for time-series data in the absence of prior knowledge of the clusters. Here we propose a...
