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- W2806886513 abstract "The paper studies on the modeling and prediction method for multi-attribute events, which exist widely in practical application. In view of the features of multi-attribute events, the paper proposes an event processing framework including the construction of training sample space based on multi-attribute event grid (MAEG), bi-direction SVR (Support Vector Regression) modeling method for prediction based on longitudinal modeling and transverse modeling, and model updating strategy based on ?-insensitive error. The performance of the proposed methods of the framework is demonstrated by extensive experiments with real datasets." @default.
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- W2806886513 date "2017-12-01" @default.
- W2806886513 modified "2023-10-17" @default.
- W2806886513 title "Multi-attribute Event Modeling and Prediction over Event Streams from Sensors" @default.
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- W2806886513 doi "https://doi.org/10.1109/icpads.2017.00110" @default.
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