Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
The study of novel detection approach for OCS dynamic parameters of high-speed electrified railway
WSEAS Transactions on Systems and Control
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The testing parameters of OCS (Overhead Contact System) are keen to evaluate the safety of electrified railway transportation and the quality of current collection between pantograph and catenary. Since the test of parameters depends on the velocity of train and the OCS conditions, carrying on systematic analysis for testing data is of great significance. In this paper, the testing data are preprocessed through centering, de-dimension and standardization first; then the classification of the testing data has been made by clustering algorithm in terms of spatial location. Thus, we could estimate the parameters appropriately and dealing with these parameters respectively according to their characteristics. The feasibility of the approach proposed is verified by the simulation results.