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Principal component analysis algorithm based compression method for data on road traffic time series

A principal component analysis and road traffic technology, applied in the field of road traffic data compression, can solve problems such as slow processing speed and complex algorithms

Inactive Publication Date: 2016-08-24
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0006] In order to overcome the disadvantages of complex algorithms and slow processing speeds in the existing road traffic data compression methods, the present invention provides a road traffic time series data compression method based on principal component analysis algorithm that simplifies the algorithm and improves the processing speed

Method used

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  • Principal component analysis algorithm based compression method for data on road traffic time series
  • Principal component analysis algorithm based compression method for data on road traffic time series
  • Principal component analysis algorithm based compression method for data on road traffic time series

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Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] refer to figure 1 and figure 2 , a road traffic time series data compression method based on principal component analysis algorithm, comprising the following steps:

[0046] 1) Obtain the road traffic projection matrix based on the historical data on the road traffic time series, the process is as follows:

[0047] Extract the historical data of the road traffic state time series in the same mode and at the same time period of the road section from the reference sequence of road traffic characteristics, and transform it into a p×q matrix, which is recorded as: A pⅹq , where p×q=n.

[0048] Matrix A pⅹq The mean of column j is:

[0049] a j = 1 p Σ i = 1 p A ...

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Abstract

A principal component analysis algorithm based compression method for data on a road traffic time series. The method comprises: firstly, based on historical data on a road traffic time series and in combination with a principal component analysis method, acquiring a projection matrix of road traffic historical data; next, based on real-time data on the road traffic time series, obtaining a road traffic data matrix; then, based on the projection matrix, acquiring a principal component of the road traffic data matrix, so as to implement compression of the real-time data on the road traffic time series; and finally, based on the principal component and the projection matrix of the road traffic data matrix, obtaining a reconstructed data matrix, so as to implement reconstruction of the real-time data on the road traffic time series. Experimental results show that the method has excellent performance on the aspect of compression of data on the road traffic time series.

Description

technical field [0001] The invention belongs to the field of road traffic data processing, relates to the analysis and compression of road traffic data, and relates to a method for compressing road traffic data. Background technique [0002] With the continuous development of intelligent transportation system data acquisition technology, based on the continuous collection of intelligent transportation data, the transportation field will soon face the problem of massive data, which must be effectively compressed before it can be processed, analyzed and stored. [0003] The inherent characteristics of traffic flow data mainly include: periodicity, similarity, correlation, etc. There are complex spatio-temporal correlations between the traffic flows of adjacent road sections, and the similarity is often high. The same traffic flow shows strong correlation and periodicity in time. These similarities indicate that there is a large amount of redundant information in the data. ...

Claims

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Application Information

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IPC IPC(8): G06F17/16
CPCG06F17/16
Inventor 徐东伟王永东张贵军李章维周晓根郝小虎丁情吴浪
Owner ZHEJIANG UNIV OF TECH
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