bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)


2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents


Best Articles 2011




Vol. 167, Issue 3, March 2014, pp. 43-49




Mining Association Rules from Airport Noise Value Among Multiple Monitoring Points

1 Fei Gu, 1, 2, 3 Tao Xu, 2, 3 Zonglei Lv

1 College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2 College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China
3 Information Technology Research Base of Civil Aviation Administration of China, Tianjin 300300, China
1 Tel: +8613290350319

1 E-mail: jintiangufei@163.com


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

Digital Sensors and Sensor Sysstems


Abstract: 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.


Keywords: Airport noise, Association rules, Monitoring points, Apriori algorithm, ATNSOA-Apriori algorithm.


Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format



Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)




Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com



Download <here> the Library Journal Recommendation Form






1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.

Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn