The rapid development of the national economy has promoted the construction of the highway in our country. With the rapid development of highway construction in China, there are also some problems, among which the most obvious one is fatigue damage of asphalt pavement. With the increasing number of vehicles, the traffic flow on the highway is also increasing sharply. With such high traffic flow, fatigue damage occurs more frequently and the average service life of highway becomes shorter. The wear condition of the road affects the sense of use of the road and also poses a threat to the safety of the vehicle to a large extent. Therefore, it is an urgent problem to predict and study the fatigue damage of asphalt pavement of expressway so as to better guide the construction of expressway in China. Based on the theory of deep learning, this paper applies the stochastic gradient descent algorithm to conduct relevant experimental research on asphalt pavement. The main damage forms of asphalt pavement at present are analyzed, and the prediction model of fatigue damage is established.


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    Titel :

    Prediction of Asphalt Pavement Fatigue Damage of Expressway Based on Deep Learning


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yang, Chao-Tung (Herausgeber:in) / Pei, Yan (Herausgeber:in) / Chang, Jia-Wei (Herausgeber:in) / Tan, Xuxiang (Autor:in) / Sun, Huadong (Autor:in) / Nan, Feng (Autor:in)

    Erschienen in:

    Innovative Computing ; Kapitel : 228 ; 1873-1880


    Erscheinungsdatum :

    2020-09-26


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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