Vehicle type identification method based on support vector machine and used for earth inductor
A technology of support vector machine and geomagnetic induction, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as good data, lack of accurate, efficient and systematic vehicle identification methods, and inability to provide quality in traffic systems , to achieve high reliability and improve efficiency
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Embodiment 1
[0038] Embodiment 1: The present invention relates to a kind of car classification recognition method based on clustering support vector machine in the single-point type geomagnetic detector, and specific process is as follows figure 1 shown. It can be roughly divided into 5 main steps:
[0039] The first step is to determine the coverage and classification mode of the classified models.
[0040] After determining the vehicle type or vehicle type combination that needs to be classified, the waveform data of the corresponding vehicle type must be collected through a single-point geomagnetic detection device.
[0041] Binary tree is selected as the classification mode of various models, such as Figure 4 As shown, that is, each classification node obtains the corresponding optimal feature combination through the feature selection method, and then learns the second-class car model samples and establishes a cluster support vector machine (C-SVM) classifier to classify the second...
Embodiment 2
[0074] (1) Determine the classified vehicle type and collect and process the data
[0075]A single-point geomagnetic detector was used to collect geomagnetic waveform samples of various vehicle types in the urban roads on the outer lanes of the south-to-north direction of the section under the inner ring elevated line (near Wuyi Road), and the geomagnetic waveform samples of various types of vehicles in the urban roads were collected. The classification of the three types of vehicles, the effectiveness of the samples were screened, and a total of 430 waveform samples of normal and undisturbed vehicle types were selected, including 360 small and medium-sized vehicles, 69 buses, and 1 large truck. An independent sample bank was established, that is, an additional 30 large truck samples were collected.
[0076] (2) Feature extraction and selection
[0077] Take the establishment of classifiers for small and medium-sized cars and large cars as an example to illustrate.
[0078] ...
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