Research on Vehicle Identification Based on Neural Network Algorithm
SHI Jun
Abstract：Aiming at the identification problem of vehicle driving,by selecting 6 typical road conditions as the initial condi?tions for each sample identification,a typical road conditions are divided into blocks to identify the sample expansion,and selected 10 to fully characterize the working characteristic and calculating parameters,characteristic parameters of every kind of typical the condition of value standard parameter vector is normalized after the formation of the corresponding neural network mode recognition model,constructing learning vector quantization of the initial condition of recognition model for effective training in order to improve the precision of the models.The neural network algorithm is completed after the training of the model,and the work condition identi?fication and simulation test are carried out under the condition of comprehensive test.The experimental results show that the trained neural network algorithm can effectively identify the actual working conditions.
Keywords：neural networklearning vector quantizationvehicle runningcondition identification
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2336-2340 )