Combination Prediction Model of Traffic Flow Based on Rough Set Theory

Gao, Hongyan; Liu, Fasheng

doi:10.1109/itcs.2009.225

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…With the increase of the traffic data, the idea of granular computing provides the traffic problems with more obvious advantages. G a o and L i u [21] which granular computing is applied into the field of intelligent transportation, proposed a combined forecasting model, based on the rough set and knowledge entropy. The relative data model in prediction and a forecasting model and decision table are established between the conversion into discrete attribute values by means of continuous attribute values.…”

Section: Development Of Grc In the Field Of Itmentioning

confidence: 99%

Granular Computing in Intelligent Transportation: An Exploratory Study

Dewen

Xinhong

Jing

et al. 2015

Cybernetics and Information Technologies

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With the continuous development of the cities, the traffic situation has gradually become a topic of concern. The concept of an intelligent transportation system has been proposed and developed. In the field of intelligent transportation, the traffic data has gradually increased. People have higher demands to real time data. The traditional data processing methods and tools have become unable to meet the needs of urban transport development. In this paper we analyzed the basic theory of granular computing, the methods, technology and current situation of granular computing. Besides, we discussed the hot issues of granular computing in an intelligent transportation system. Finally, granular computing in the development of intelligent transportation fields was also discussed.

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Section: Development Of Grc In the Field Of Itmentioning

confidence: 99%