Traffic Prediction System Utilizing Application and Control of Environmental Information
In the inference analysis using structured data, it can be thought that the analysis is easy because the meaning of the formal data can be accurately determined. However, it can be very difficult to predict the area whose data is sensitive to the surrounding environment such as traffic volume. To solve this problem, we proposed a system which improved the traffic volume reliability by finding the specific events that affect the traffic volume by applying the unstructured data. However, there is a difficult problem replacing with the appropriate data in the present system. To address this problem, in this paper, we show that the accurate traffic amount can be estimated by applying the most similar data through correlation analysis.
KeywordsFCM Fuzzy inference LSA Correlation analysis Traffic volume
This research was supported by the Research Grant of Pukyong National University (2017 year).
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