
AbstractBased on efficient continuous parallel query series algorithm supporting multi-objective optimization, by using visual graphics technology for traffic data streams for efficient real-time graphical visualization, it improve human-computer interaction, to realize real-time and visual data analysis and to improve efficiency and accuracy of the analysis. This paper employs data mining processing and statistical analysis on real-time traffic data stream, based on the parameters standards of various data mining algorithms, and by using computer graphics and image processing technology, converts graphics or images and make them displayed on the screen according to the system requirements, in order to track, forecast and maintain the operating condition of all traffic service systems effectively.
Big Data, Smart Transportation, Cloud Computing, Parallel Query, Engineering(all), Visualization
Big Data, Smart Transportation, Cloud Computing, Parallel Query, Engineering(all), Visualization
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