14 Result(s)
within
**ongjie Jia
Computer Science
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Article
An Efficient Cloudlet Deployment Method Based on Approximate Graph Cut in Large-scale WMANs
Mobile edge computing provides a low-latency, high-bandwidth cloud computing environment for resource-constrained mobile devices by allowing mobile devices to offload tasks, but user task migration causes grea...
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Chapter and Conference Paper
Research on the Application of Digital Technology in Civil Engineering Survey Management System
With the continuous development of science and technology, computer digital measurement technology develops rapidly. In engineering measurement, digital measurement technology plays a very important role, It i...
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Chapter and Conference Paper
Large-Scale Spectral Clustering with Stochastic Nyström Approximation
In spectral clustering, Nyström approximation is a powerful technique to reduce the time and space cost of matrix decomposition. However, in order to ensure the accurate approximation, a sufficient number of s...
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Chapter and Conference Paper
An Approach to Propose Optimal Energy Storage System in Real-Time Electricity Pricing Environments
Based on the fact that the penetration of renewable energies is increasing dramatically, almost all the energy markets have changed and taken action to present the strategy of real-time pricing over the last d...
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Chapter and Conference Paper
A K-AP Clustering Algorithm Based on Manifold Similarity Measure
K-AP clustering algorithm is a kind of affinity propagation (AP) clustering that can directly generate specified K clusters without adjusting the preference parameter. Similar to AP clustering algorithm, the clus...
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Article
An Adaptive Density Data Stream Clustering Algorithm
Now we are in the age of big data. Huge amount of data and information are generated every time. Traditional data stream algorithms are suit for the data streams with low dimension and simple structure. Howeve...
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Chapter and Conference Paper
p-Spectral Clustering Based on Neighborhood Attribute Granulation
Clustering analysis is an important method for data mining and information statistics. Data clustering is to find the intrinsic links between objects and describe the internal structures of data sets. p-Spectral ...
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Article
Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors
Cognitive computing needs to handle large amounts of data and information. Spectral clustering is a powerful data mining tool based on algebraic graph theory. Because of the solid theoretical foundation and go...
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Article
Research on data stream clustering algorithms
Data stream is a potentially massive, continuous, rapid sequence of data information. It has aroused great concern and research upsurge in the field of data mining. Clustering is an effective tool of data mini...
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Article
A density-adaptive affinity propagation clustering algorithm based on spectral dimension reduction
As a novel clustering method, affinity propagation (AP) clustering can identify high-quality cluster centers by passing messages between data points. But its ultimate cluster number is affected by a user-defi...
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Article
The latest research progress on spectral clustering
Spectral clustering is a clustering method based on algebraic graph theory. It has aroused extensive attention of academia in recent years, due to its solid theoretical foundation, as well as the good performa...
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Article
Granular neural networks
Fuzzy neural networks (FNNs) and rough neural networks (RNNs) both have been hot research topics in the artificial intelligence in recent years. The former imitates the human brain in dealing with problems, th...
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Article
Research of semi-supervised spectral clustering algorithm based on pairwise constraints
Clustering is often considered as an unsupervised data analysis method, but making full use of the prior information in the process of clustering will significantly improve the performance of the clustering al...
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Article
Research of semi-supervised spectral clustering based on constraints expansion
Semi-supervised learning has become one of the hotspots in the field of machine learning in recent years. It is successfully applied in clustering and improves the clustering performance. This paper proposes a...
