可视分析增强的平行智能交通系统框架

随着人工智能2.0时代的到来,可视分析方法作为一种重要的人机耦合方法受到越发广泛的关注.其是大数据分析的利器,也是理解数据的"导航仪",能够有效地将三元空间结构(CPH)中的数据转换为知识系统中的服务与决策,从而进一步提升交通系统智能化水平.为此,提出人工交通系统、计算实验和平行执行相融合的平行智能交通系统,为智能交通...

Parallel intelligent transportation system framework enhanced byvisual analysis

With the advent of artificial intelligence 2.0 era, visual analysis methods have received more and moreattention as an important human-machine coupling method. It is a powerful tool for big data analysis anda“navigator”for understanding data. It can effectively convert data in a ternary spatial structure (cyber-physical-human,CPH) into services and decision-making in a knowledge system, thereby further enhancing the intelligent level oftransportation system. At the same time, a parallel intelligent transportation system that integrates artificialtransportation system, computational experiment and parallel execution is proposed, which provides a new mechanismand new mode of manipulation in the field of intelligent transportation. Through the analysis of specific cases, wediscuss the importance of visual analysis in the new generation of artificial intelligence, and the process transformingdata or information into knowledge systems. It is proved that the seamless combination of visual analysis and parallelintelligent transportation system can better analyze large-scale traffic data, solve traffic problems more effectively, andachieve the enhancement effect of “1+1>2”. Based on this, a novel parallel intelligent transportation system framework enhanced by visual analysis is proposed.