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Vol. 167, Issue 3, March 2014, pp. 68-74

 

Bullet

 

Research of the Space Clustering Method for the Airport Noise Data Minings
 

1, 2 Jiwen Xie, 1, 2 Tao Xu, 2 Guoqing Yang

1 College of Computer Science and Technology, Civil Aviation University of China, Tianjin, China
2 Information Technology Research Base, Civil Aviation Administration of China, Tianjin, China
1 Tel.: 15922191232, fax: 022-24092286

E-mail: xiejiwenpower@163.com

 

Received: 20 December 2013 /Accepted: 28 February 2014 /Published: 31 March 2014

Digital Sensors and Sensor Sysstems

 

Abstract: Mining the distribution pattern and evolution of the airport noise from the airport noise data and the geographic information of the monitoring points is of great significance for the scientific and rational governance of airport noise pollution problem. However, most of the traditional clustering methods are based on the closeness of space location or the similarity of non-spatial features, which split the duality of space elements, resulting in that the clustering result has difficult in satisfying both the closeness of space location and the similarity of non-spatial features. This paper, therefore, proposes a spatial clustering algorithm based on dual-distance. This algorithm uses a distance function as the similarity measure function in which spatial features and non-spatial features are combined. The experimental results show that the proposed algorithm can discover the noise distribution pattern around the airport effectively.

 

Keywords: Airport noise, Data mining, Distribution pattern of the airport noise, Dual-distance, Spatial clustering algorithm.

 

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