Abstract
In view of the traffic flow data of non-stationary, the abnormal data detection is difficult.proposed basing on the wavelet analysis and least squares method of abnormal traffic flow data detection in this paper.First using wavelet analysis to make the traffic flow data of high frequency and low frequency component and separation, and then, combined with least square method to find abnormal points in the reconstructed signal data.Wavelet analysis and least square method, the simulation results show that using wavelet analysis of abnormal traffic flow data detection, effectively reduce the detection results of misjudgment rate and false negative rate.
Highlights
The supply of the existing urban transportation infrastructure cannot meet the needs of the current urban development on the road, which is he main reason that caused by traffic congestion in the great cities of the world, traffic safety, and environmental pollution
Wavelet multi-resolution analysis feature to signal under the different scales of multiresolution decomposition, and intertwined in different frequency of mixed signal is decomposed into different frequency band signal, so the signal has the ability of press band processing
Selection based on the least square method of wavelet analysis to analyze traffic signal, choose db[3] wavelet as the wavelet basis function, the traffic signal 2 layers wavelet decomposition scale, and after wavelet decomposition of the low frequency part of the refactoring, the original traffic signal and reconstructing low frequency signal is shown in figure 2: 01090-p.2 analysis of abnormal traffic flow data detection more accurate and effective
Summary
The supply of the existing urban transportation infrastructure cannot meet the needs of the current urban development on the road, which is he main reason that caused by traffic congestion in the great cities of the world, traffic safety, and environmental pollution. More advanced, more widely used a traffic management technology is intelligent transportation system (ITS). It through the use of advanced electronic, information, sensor and system engineering, and other technology integration and application based on relatively perfect road facilities to satisfy the actual demand of ground transportation. Equipment failure, traffic control and other reasons will often cause the lack of data acquisition and error phenomenon. The abnormal traffic flow data detection is an essential work
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