带有同步预测的WBAN时序数据融合算法

doi:10.11959/j.issn.1000-436x.2015147

Abstract

Abstract:

Due to the nonlinearity and nonstationarity of the physiological data sensed by WBAN,data aggregation cannot be effectively achieved according to the time-domain trend of data.Therefore,a novel time series data aggregation algorithm with synchronous prediction was proposed.By preprocessing the original sensing data with the multi-resolution analysis,the inherent characteristics of the physiological data can be obtained to establish a light-weight synchronous prediction model at both the sensor and sink.Numerical results show that the proposed aggregation algorithm can achieve a favorable prediction precision and a low energy consumption rate by eliminating the in-network data redundancy.

Key words: wireless body area network, data aggregation, multi-resolution analysis, LSSVM, synchronous prediction mechanism

Ru-yan WANG,Mei-ling ZHAI,Da-peng WU. Time series data aggregation algorithm with synchronous prediction for WBAN[J]. Journal on Communications, 2015, 36(6): 13-21.

Figures/Tables 11

References 27

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数据融合算法	每次预测耗时/s	RMSE	能耗增益/%
WT-LSSVM	0.838 4	0.052 9	57.708 3
LSSVM	0.305 5	0.363 3	69.583 3
SVM	4.922 6	0.044 7	53.750 0
Kalman	0.001 5	0.265 6	84.583 3

Time series data aggregation algorithm with synchronous prediction for WBAN

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