The research based on the vehicle accidents steps to collect and structure a progressive secure transportation but unfortunately, vehicle crashes were unavoidable. The accident prediction related to the risky environment data collection and arrangements based on the high priority of reality of accidents. The social activity and roadway structures are useful in the progression of traffic security control approach. We believe that to secure the best possible setback decline impacts with limited budgetary resources, it is basic that measures be established on coherent and objective studies of the explanations behind mishaps and seriousness of wounds. A survey based on the different algorithms able to predict the road accidents prevention methods. This paper demonstrates a couple of models are predicting the reality of harm that occurred in the midst of car accidents using three artificial intelligent approaches (AI). The proposed scheme contributes neural systems prepared utilizing choice trees and fluffy c implies bunching strategy for division.


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    Titel :

    A Pavement Mishap Prediction Using Deep Learning Fuzzy Logic Algorithm


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Peng, Sheng-Lung (Herausgeber:in) / Son, Le Hoang (Herausgeber:in) / Suseendran, G. (Herausgeber:in) / Balaganesh, D. (Herausgeber:in) / Priya, V. (Autor:in) / Priya, C. (Autor:in)


    Erscheinungsdatum :

    18.11.2021


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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