Study on Machine Learning Model for Comprehensive Evaluation of Rail Traffic Safety
نویسندگان
چکیده
In recent years, the rail transport has achieved rapid development. In assuming the responsibility of promoting the transport task of the economic development, it also faces greater challenges of the rapid growth of passenger volume and safety guarantee. To carry out research on rail traffic safety assessment has essential theoretical and practical significance in protecting public property and personal safety, promoting the development of city rail traffic, enhancing their level of service, and preventing and reducing accidents. The machine learning technology and security data index generated by traditional structured data are used to integrate, a comprehensive assessment model is adopted to study rail traffic safety state from a new perspective, which provides technical support for the comprehensive evaluation of railway transportation safety and provides decision support for rail transit operation.
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