Study on Temperature Related Factors of Asphalt Pavement Based on APRIORI. Issue 1 (February 2020)

• Record Type: Journal Article
• Authors: Lin, W Y; Zhang, Z H; Qiu, X; Xu, W Y; Hong, H J
• Is Part Of: IOP conference series. Volume 758:Issue 1(2020)
• Publication Date: 2020-02
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/758/1/012030
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Asphalt is a typical temperature-sensitive material. In order to explore the correlation between surface temperature of asphalt pavements and meteorological factors, the association rules mining algorithm (Apriori) was applied to identify the key factors affecting the surface temperature of asphalt pavement. Firstly, errors and missing data in the meteorological dataset were cleaned. Then, Apriori was applied to identify the key factors affecting the asphalt pavement temperature. The results indicate that Apriori would perform an excellent ability to analyze the correlation rules between meteorological factors with the minimum confidence of 0.8 and the key meteorological factors which affect the temperature change of asphalt pavements are excavated including air temperature, air pressure, dew point temperature and relative humidity. The research would serve as a technical support for the machine learning algorithms applied in the field of the association rule analysis.