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Cluster Analysis

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Structure enhanced deep clustering network via a weighted neighbourhood auto-encoder.

Neural networks : the official journal of the International Neural Network Society
Structural deep clustering involves the use of neural networks for fusing semantic and structural representations for clustering tasks, and it has been receiving increasing attention. In some pioneering works, auto-encoder (AE)-specific representatio...

A Fast Weighted Fuzzy C-Medoids Clustering for Time Series Data Based on P-Splines.

Sensors (Basel, Switzerland)
The rapid growth of digital information has produced massive amounts of time series data on rich features and most time series data are noisy and contain some outlier samples, which leads to a decline in the clustering effect. To efficiently discover...

A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels.

Sensors (Basel, Switzerland)
Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data play a significant role in tracking vessel activity and mapping mobility patterns s...

Multi-Kernel Fuzzy Clustering-Based Sporting Consumption Behavior Study.

Computational intelligence and neuroscience
Cluster analysis plays a very important role in the field of unsupervised learning. The multikernel function is used to transform the low-dimensional nonlinear relationship of the influencing factors of consumption behavior into a high-dimensional li...

Risk assessment of interstate pipelines using a fuzzy-clustering approach.

Scientific reports
Interstate pipelines are the most efficient and feasible mean of transport for crude oil and gas within boarders. Assessing the risks of these pipelines is challenging despite the evolution of computational fuzzy inference systems (FIS). The computat...

Research on Clustering Algorithm Based on Improved SOM Neural Network.

Computational intelligence and neuroscience
Clustering algorithm is a statistical method to study sample classification. With the rapid development of science and technology, people have higher and higher requirements for data classification, so there are more and more researches on clustering...

A benchmark study of deep learning-based multi-omics data fusion methods for cancer.

Genome biology
BACKGROUND: A fused method using a combination of multi-omics data enables a comprehensive study of complex biological processes and highlights the interrelationship of relevant biomolecules and their functions. Driven by high-throughput sequencing t...

Wetland Ecotourism Development Using Deep Learning and Grey Clustering Algorithm from the Perspective of Sustainable Development.

Journal of environmental and public health
The purpose is to promote the sustainable development of wetland ecotourism in China and plan the passenger flow in different tourism periods. This work selects Zhangye Heihe wetland ecotourism spot as the research object. Firstly, the two single wet...

Construction of the Public Management Performance Assessment Algorithm Using Fuzzy Clustering.

Journal of environmental and public health
This paper analyzes the limitations of the current public management performance evaluation system, puts forward a public management performance evaluation model based on fuzzy clustering, and expounds on the theoretical framework and principle of th...

Optimization of Choreography Teaching with Deep Learning and Neural Networks.

Computational intelligence and neuroscience
To improve the development level of intelligent dance education and choreography network technology, the research mainly focuses on the automatic formation system of continuous choreography by using the deep learning method. Firstly, it overcomes the...