Smart vehicle frames have many special uses and frameworks designed toimprove road safety and productivity. We are experiencing rapid advances in advancedInter Vehicular Communication (IVC) designed by Intelligent Transportation Systems(ITS) to allow the collection, evaluation, and dissemination of applicable data. Theseframeworks allow you to screen, monitor, and control different parts of the road. Themain research to regulate the behavior of the driver is focused on two issues: theformation of identifiable patterns in the test and the grouping of the characteristics ofthe driver's behavior. In this research proposal, we will have a layout of a Rule-BasedFuzzy Polynomial Neural Networks system based on their behavior in differentprofiles. Given our reproductive system, we have had the opportunity to speakaccurately with the control model, but the main probability models show that theobserver rating works relatively well with the sophisticated models.


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    Titel :

    Intelligent Transportation Systems-based Behavior Characteristics Classification


    Beteiligte:
    Rani, B.M.S. (Autor:in) / Lydia, E. Laxmi (Autor:in) / Moses, G. Jose (Autor:in)


    Erscheinungsdatum :

    2021



    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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