The invention provides a grid fault diagnosis method based on data mining. The method comprises the steps of establishing a multidimensional data model and a fault fact table, conducting clustering analysis on fault data, conducting association rule analysis on the fault data, conducting Bayesian ...
Most data stream clustering methods are not capable of dealing with high dimensional data streams; therefore they sacrifice the accuracy of clusters. In order to solve this problem we proposed an adaptive grid -based clustering method. Our focus is on providing up-to-date arbitrary shaped clusters...
A grid-based data clustering method is disclosed. A parameter setting step sets a grid parameter and a threshold parameter. A diving step divides a space having a plurality of data points according to
Intro Algo Ref Intro k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition...谱聚类算法(Spectral Clustering)优化与扩展 谱聚类(Spectral Clustering, SC)在前面的博文中已经详...
Primitive-Based Grids At first pass, it may seem that the primitive-based grid generation of FLAC3D is limited to rather simple, regular-shaped regions. In the introductory sections, the examples provided are often uniform, polyhedral grids. FLAC3D primitive shapes, however, can be distorted to ...
The ensemble learning model has been employed in this case. Ensemble learning is a data mining technology, also known as the committee method or model combiner, which combines the strengths of many models to generate better predictions and efficiency than each model alone. In our system, we use...
His master’s thesis proposed a method to optimize channel switching in digital television and was awarded an Alcatel Master of Science Innovation Award. Since October 2006, he has been employed by the Interdisciplinary Institute for BroadBand Technology (IBBT), and is working with the Department ...
5. On density-based and representative-based spatial clustering algorithms. [D] . Chen, Chun-Sheng. 2011 机译:基于密度和基于代表的空间聚类算法。 6. Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi [O] . Chuan Li, Lin Li, Ji...
In this case, for any input, each CEj receives all the input components, but A novel parallel clustering method: the Weight Recombining (WR) PSOM In order to parallelize the Kohonen’s algorithm we propose an approach based on data partition and Weight Recombining (WR) to be executed in ...
The method is embedded in Pareto-based and indicator-based MOEA, and the results show that this method significantly improves the performance of Pareto-based MOEA on reducible and nonreducible MaOP. But it is not very helpful to the performance of indicator-based MOEA [8]. Chaoliang et al....