Abstract

In order to improve the accuracy and efficiency of the vehicle network security situation prediction, a prediction algorithm based on improved CLPSO-RBF is proposed. Firstly, for speeding up the optimization efficiency of CLPSO, a reasonable speed monitoring variable has been introduced. Secondly, we use the improved CLPSO algorithm to optimize the clustering radius of the RBF neural network, so that the optimal RBF network structure can be determined. Finally, we use the optimal RBF network to predict the security situation of the vehicle network. Simulation experiments have proved that the improved algorithm has higher accuracy and faster convergence rate in situation prediction, and has better prediction effects.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.