An Anomaly Detection Method of Airport-noise Time Series #br# Based on Improved SAX Measurement

doi:10.3969/j.issn.1006-2475.2014.08.002

Abstract

Abstract: With the expansion of airport transportation scale, the airport noise issue is becoming one of the obstacles for the sustainable development of the aviation industry. Anomalies in the airport noise are of great significance for the timely improvement of the equipments of aircraft and airports. In this paper, according to the characteristics of airport noise, a time series anomaly detection method for single monitoring point is proposed, which is based on the improved symbolic aggregate approximation similarity measurement. This method calculates the measure by applying the improved similarity measure, and finally finds anomalies using the k-nearest neighbor anomaly detection method. The proposed method is applied in practice after the theoretical verification of its feasibility.

Key words: airport-noise time series, improved similarity measurement, single monitoring point, outlier factor, anomaly detection

CLC Number:

TP311.131

WANG Wei, WANG Jian-dong, ZHANG Xia. An Anomaly Detection Method of Airport-noise Time Series #br# Based on Improved SAX Measurement[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.08.002.

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