Mining Association Rules from Airport Noise Value Among Multiple Monitoring Points

Sensors & Transducers

Zonglei Lv¹  Fei Gu²  Tao Xu² 

[1] College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China ;College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China ;

关键词: Airport noise;    Association rules;    Monitoring points;    Apriori algorithm;    ATNSOA-Apriori algorithm.;   

DOI  :  

来源: DOAJ

【 摘 要 】

There are a lot of links among monitoring points of airport noise. To mine association rules among these monitoring points is very important in order to predict airport noise scientifically and effectively. Due to the low efficiency of the Apriori algorithm for mining association rules, this paper proposes a new algorithm called 'Adapt to Noise Set of Airport-Apriori (ATNSOA- Apriori)'. According to the characteristics of monitoring data sets of airport noise, this algorithm optimizes the monitoring data to improve the validity of the monitoring data sets and uses arrays to store items to lower the number of traversing database. As a result, the efficiency of mining association rules is improved. Taking the actual noise monitoring data in a domestic airport in China for example, the experimental results show that the ATNSOA - Apriori algorithm can deal with monitoring data sets of airport noise more effectively and mine the useful association rules more quickly. The proposed algorithm, therefore, is of vital significance for predicting the value of monitoring points and evaluating the effectiveness of the value of monitoring points.

【 授权许可】

Unknown