Real-Time Risk Assessment for Road Transportation of Hazardous Materials Based on GRU-DNN with Multimodal Feature Embedding

Real-Time Risk Assessment for Road Transportation of Hazardous Materials Based on GRU-DNN with Multimodal Feature Embedding

In this paper, a gated recurrent unit–deep neural network (GRU-DNN) model integrated with multimodal feature embedding (MFE) is developed to evaluate the real-time risk of hazmat road transportation based on various types of data for contributing factors. MFE was incorporated into the framework of a...

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Bibliographic Details
Main Authors: Shanchuan Yu, Yi Li, Zhaoze Xuan, Yishun Li, Gang Li
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Applied Sciences
Subjects:
risk assessment
hazardous materials transportation
deep neural network
multimodal feature embedding
adversarial attack
Online Access:https://www.mdpi.com/2076-3417/12/21/11130

Internet

https://www.mdpi.com/2076-3417/12/21/11130

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