关键词: 无线传感器;离群点检测;数据融合;贝叶斯算法

Abstract:

With the rapid development of wireless sensor network,the amount of data acquisition as well as the dimensions of data increases constantly.However,the existing outlier detection algorithms are mostly used for single or low dimensional data.This paper presents an outlier detection technique based on Fusion-Bayes.This method first uses the data fusion to converse data from different sources into the same form,and then uses a Bayesian method to detect outliers of different attributes.Experiments show multidimensional data attribute fusion detection is more accurate and the more effective compared to the single dimension attribute or low dimension attribute detection.

Key words: wireless sensor network;outlier detection;data fusion;Bayes algorithm