4.5 Article

SS-ITS: secure scalable intelligent transportation systems

期刊

JOURNAL OF SUPERCOMPUTING
卷 77, 期 7, 页码 7253-7269

出版社

SPRINGER
DOI: 10.1007/s11227-020-03582-7

关键词

Blockchain Learning; Reinforcement Learning; Anomaly Detection; GPU; Intelligent Transportation

向作者/读者索取更多资源

This paper presents a secure and scalable intelligent transportation and human behavior system that utilizes blockchain technology and efficient GPU processing, with a reinforced deep learning algorithm to merge local knowledge into global knowledge. Experimental results demonstrate its superiority over baseline solutions in outlier detection.
This paper introduces a secure and scalable intelligent transportation and human behavior system to accurately discover knowledge from urban traffic data. The data are secured using blockchain learning technology, where the scalability is ensured by a threaded GPU. In addition, different optimizations are provided to efficiently process data on the GPU. A reinforcement deep learning algorithm is also established to merge local knowledge discovered on each site into global knowledge. To demonstrate the applicability of the proposed framework, intensive experiments have been carried out on well-known intelligent transportation and human behavior data. Our results show that our proposed framework outperforms the baseline solutions for the outlier detection use case.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据