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- W2365719705 abstract "In order to coofigure communication system efficiently, it is necessary to predict the traffic, which has the characteristic of following various rules in different date. This paper proposes time series prediction by Case-based nearest neighbor algorithm and make improvements on considering dynamic length of time series, extracting charac- teristic from time series and selecting nearest case, with which ideal results can be achieved. Being applied to Guang- dong Telecommunications Network Intelligent Management System (GTNIMS), the nearest neighbor algorithm can provide fast, accurate prediction traffic for routing solution and set the stage for more precise solution." @default.
- W2365719705 created "2016-06-24" @default.
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- W2365719705 date "2005-01-01" @default.
- W2365719705 modified "2023-09-23" @default.
- W2365719705 title "Apply Nearest Neighbor Algorithm to Traffic Time Series Prediction" @default.
- W2365719705 hasPublicationYear "2005" @default.
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