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Novel Wavelet-mFCM Algorithm for Environmental Sensor Drift Correction
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DOI：10.1109/JSEN.2013.2254112.png)
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摘要
En 中文
A novel hybrid sensor informatics architecture based on discrete wavelet transform (DWT) and multiple fuzzy logic based clustering (m-FCM) is investigated and proposed to estimate sensor drift in a real life oceanic sensor network. DWT is used for sensor pre-processing, data dimension reduction and feature extraction from sensor time series, where as FCM-based approach is used to estimate and correct the cumulative drift in the sensory system. This new drift correction algorithm is tested on a real time estuary sensory platform deployed to monitor the Derwent Estuary in Hobart, Australia, to evaluate the performance. This algorithm outperforms previously reported drift correction paradigms.
Keyword:
Component analysis
discrete wavelet
drift area
Fuzzy C means
principal sensor drift
transform
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期刊
IF:
4.5
论文数:
2.2W
被引数:
7.3W
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