This study put forward a generalized risk-entropy model in order to describe the complexity of Yangtze River waterway transport safety system, with the application of dynamic theory of energy transmission in nonlinear systems, and analysis methods for complex systems. The generalized risk-entropy model can characterize the overall risk evolution mechanism of the emergence promoted by risk network communication, superposition coupling, and level transition in waterway transport safety system. The method of artificial neural network is used to identify the model of generalized risk-entropy model, a BP neural network model is constructed for Yangtze River waterway transport risk assessment based on generalized risk-entropy. After that, waterway transport safety early warning management system framework, function structure, and logic structure, etc. are designed, and an early warning management system is developed for application demonstration in Wuhan waterway section. It hopes to provide a new idea and method for the risk prediction, evaluation, and early warning management of waterway transportation system.


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    Titel :

    Yangtze River Waterway Transportation Safety Early Warning Management System Based on Generalized Risk-Entropy


    Beteiligte:
    Zhang, Shiyu (Autor:in) / Yang, Yuhao (Autor:in) / Ke, Jiangcen (Autor:in) / Wang, Chuang (Autor:in)

    Kongress:

    Sixth International Conference on Transportation Engineering ; 2019 ; Chengdu, China


    Erschienen in:

    ICTE 2019 ; 495-503


    Erscheinungsdatum :

    13.01.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch