DocumentCode :
2556229
Title :
Comparison of CART-based localization and SVMs-based localization in WSN
Author :
Zhou, Wenyong ; Liu, Chunhua ; Liu, Hongbing
Author_Institution :
Sch. of Comput. & Inf. Technol., Xinyang Normal Univ., Xinyang, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
340
Lastpage :
343
Abstract :
Localization of sensor nodes is essential for wireless sensor network when it is applied to the special applications. We formed two models to estimate the location of sensor nodes, CART-based localization and SVMs-based Localization. During the training process, the received signal strength of the reference nodes is selected as the input of two models and the location information is regarded as the output of two models. During the localization process, the decision trees of CART and support vector machines are used to estimate the location of blindfolded nodes. We demonstrate the practicality and feasibility of the two models through simulations in the 100m×100m area.
Keywords :
decision trees; support vector machines; telecommunication computing; wireless sensor networks; CART based localization; SVM based localization; WSN; blindfolded node location; location information; sensor node localization; signal strength; support vector machines; wireless sensor network; Accuracy; Base stations; Data models; Kernel; Mathematical model; Training; Wireless sensor networks; localization; received signal strength; regression; support vector machines; wireless sensor network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234509
Filename :
6234509
Link To Document :
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