Bat algorithm support vector machine-based highway traffic state recognition method

A technology of support vector machines and highways, which is applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc., and can solve problems such as affecting classification accuracy.

Active Publication Date: 2018-11-06
GUANGDONG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

The parameter setting of the support vector machine affects its classification accuracy.

Method used

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  • Bat algorithm support vector machine-based highway traffic state recognition method
  • Bat algorithm support vector machine-based highway traffic state recognition method
  • Bat algorithm support vector machine-based highway traffic state recognition method

Examples

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Embodiment 1

[0067] The present invention is embodied in the highway traffic state recognition of a certain city in Guangdong Province, and its steps are as follows:

[0068] S1. Acquire the one-week expressway parameter data collected by a certain expressway monitoring system in Guangdong Province, and use the maximum-minimum standardization process. Including: weather conditions, traffic flow, time average speed, time occupancy rate. The daily collection time is: 00:00-23:55, the time interval is 5 minutes, a total of 2016 sets of valid data. Among them, the weather condition is represented by w, w∈[0,1], the better the weather condition, the larger the value. Optional: sunny, w=1; cloudy, w=0.8; light rain, w=0.6; misty, w=0.4; moderate rain, w=0.3.

[0069] S2. Obtain the traffic operation status data of the expressway, and quantify it. Set the traffic status level, the better the road operation status, the lower the level. Optionally, the traffic state is set to 5 levels, smooth=1...

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Abstract

The invention relates to a bat algorithm support vector machine-based highway traffic state recognition method. The method includes the following steps that: S1, traffic state parameter data and running state data are obtained, and data sets are divided into a training set and a test set; S2, the parameters of a support vector machine are set, a bat population is constructed and initialized, an optimal bat position and a fitness value are calculated; S3, bat algorithm parameters are updated, a random number is generated for each bat individual, if rand1 is larger than R<t>i, random disturbanceis generated near an optimal solution, thus, the method shifts to local search; S4, a genetic algorithm is adopted to optimize the bat individuals; S5, a random number is generated for each bat individual, if rand2 is smaller than A<t>i, and fi is larger than f<*>, a pulse rate and loudness are updated; S6, the bats are rearranged, so that an xbest is obtained, whether a maximum number of iterations is reached is judged, and the optimal penalty parameters c and g of the support vector machine are determined; and S7, the training set is inputted into the support vector machine model so as to perform training, and an outputted predicted state is compared with the state of the test set, so that recognition accuracy can be calculated.

Description

technical field [0001] The invention relates to a highway traffic state recognition method, in particular to a highway traffic state recognition method based on a bat algorithm support vector machine. Background technique [0002] With the increase of highway traffic demand, traffic congestion, traffic accidents, tail gas pollution and other problems continue to increase, seriously endangering road traffic safety. The research on traffic status recognition enables these problems to be presented in a predictable way, providing dynamic decision-making basis for traffic participants and commanders. The research methods of traffic state recognition are roughly divided into direct method and indirect method. The early artificial traffic evacuation and the method of identifying traffic state through video image monitoring belong to the direct method; The traffic state method belongs to the indirect method. [0003] Support vector machine (Support Vector Machine, SVM) has the cha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
CPCG08G1/0133
Inventor 蔡延光王锦添蔡颢
Owner GUANGDONG UNIV OF TECH
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