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应用语义web技术诊断道路交通拥堵

Applying SemanticWeb Technologies for Diagnosing Road Traffic Congestions
课程网址: https://videolectures.net/videos/semantic_lecue_road_congestions  
主讲教师: Freddy Lecue
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2012-12-10
课程语种: 英语
中文简介:
诊断,或将原因与结果联系起来的方法,是一项重要的推理任务,可以深入了解城市,实现当今所设想的可持续和智慧城市的概念。本文以交通运输及其道路交通为研究对象,介绍了如何实现道路交通拥堵的准实时检测和诊断。我们采用纯人工智能诊断技术,充分利用通过相关语义增强流和来自各个领域的静态数据捕获的知识。我们在爱尔兰都柏林进行的道路交通拥堵语义感知诊断的原型,有效地处理了大量异构信息源,并以准实时的方式为市民和城市管理者提供增值服务。
课程简介: Diagnosis, or the method to connect causes to its effects, is an important reasoning task for obtaining insight on cities and reaching the concept of sustainable and smarter cities that is envisioned nowadays. This paper, focusing on transportation and its road traffic, presents how road traffic congestions can be detected and diagnosed in quasi real-time. We adapt pure Artificial Intelligence diagnosis techniques to fully exploit knowledge which is captured through relevant semantics-augmented stream and static data from various domains. Our prototype of semantic-aware diagnosis of road traffic congestions, experimented in Dublin Ireland, works efficiently with large, heterogeneous information sources and delivers value-added services to citizens and city managers in quasi real-time. 
关 键 词: 交通堵塞; 异构信息源; 人工智能诊断技术
课程来源: 视频讲座网
数据采集: 2025-04-28:zsp
最后编审: 2025-04-28:zsp
阅读次数: 6