Patent ID: 11863397
Assignee: ZTE CORPORATION
Field: Digital communication (Electrical engineering)
Classification: CPC H | IPC H

Claim 7:
8. A traffic prediction device, comprising:
at least one processor; and,
a memory communicatively connected to the at least one processor; wherein,
the memory stores an instruction executable by the at least one processor, wherein the instruction, when executed by the at least one processor, causes the at least one processor to perform a traffic prediction method, wherein the traffic prediction method comprises:
acquiring and preprocessing traffic data of a first preset time period in a historical period to obtain preprocessed traffic data;
performing empirical mode decomposition on the preprocessed traffic data to obtain a plurality of component series;
using a time series prediction model to fit the plurality of component series to obtain a plurality of fitted component series, and using the plurality of fitted component series to obtain a plurality of component prediction results for a second preset time period; and
accumulating the plurality of component prediction results to obtain a traffic prediction result for the second preset time period[H]i
wherein using the time series prediction model to fit the plurality of component series to obtain a plurality of fitted component series, and using the plurality of fitted component series to obtain the plurality of component prediction results for the second preset time period, comprises:
 with respect to each component series of the plurality of component series:
 decomposing the each component series into a trend term, a seasonal term and a noise term, such that the each component series is represented by a sum of the trend term, the seasonal term and the noise term;
 determining a fitted trend item and a fitted seasonal item respectively, and then using the fitted trend item and the fitted seasonal item to obtain a trend item prediction result and a seasonal item prediction result for the second preset time period; and
 accumulating the trend item prediction result, the seasonal item prediction result and the noise item to obtain a component prediction result of the each component series for the second preset time period.