DocumentCode :
2975524
Title :
Target Localization Using Ensemble Support Vector Regression in Wireless Sensor Networks
Author :
Kim, Woojin ; Park, Jaemann ; Kim, H. Jin
Author_Institution :
Sch. of Aerosp. & Mech. Eng., Seoul Nat. Univ., Seoul, South Korea
fYear :
2010
fDate :
18-21 April 2010
Firstpage :
1
Lastpage :
5
Abstract :
This paper considers a target localization problem whose goal is to estimate the location of an unknown object. It is one of the key issues in applications of wireless sensor networks (WSNs). With recent advances in fabrication technology, deployment of a large WSNs has become economically feasible. On the other hand, this has caused the curse of dimensionality in applying learning algorithms such as support vector regression (SVR). To handle this, we use an ensemble implementation of SVRs for target localization and validate it experimentally. This paper draws a comparison between the conventional SVR method and the proposed method in terms of the accuracy and robustness. Experimental results show that the prediction performance of the proposed method is more accurate and robust to the measurement noise than conventional SVR predictor.
Keywords :
regression analysis; wireless sensor networks; ensemble support vector regression; fabrication technology; target localization; wireless sensor networks; Acoustic sensors; Biomedical measurements; Biomedical monitoring; Learning systems; Machine learning; Noise measurement; Noise robustness; Peer to peer computing; Sensor phenomena and characterization; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications and Networking Conference (WCNC), 2010 IEEE
Conference_Location :
Sydney, NSW
ISSN :
1525-3511
Print_ISBN :
978-1-4244-6396-1
Type :
conf
DOI :
10.1109/WCNC.2010.5506589
Filename :
5506589
Link To Document :
بازگشت