S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Mechanical Aerospace Engineering (기계항공공학부) Journal Papers (저널논문_기계항공공학부)
Target Localization Using Ensemble Support Vector Regression in Wireless Sensor Networks
- Kim, Woojin; Park, Jaemann; Yoo, Jaehyun; Kim, H. Jin; Park, Chan Gook
- Issue Date
- IEEE Transactions on Cybernetics, Vol.43 No.4, pp. 1189-1198
- 공학; Ensemble support vector regression (SVR); target localization; wireless sensor networks(WSNs)
- Target localization, whose goal is to estimate the location of an unknown target, is one of the key issues in applications of wireless sensor networks (WSNs). With recent advances in fabrication technology, deployments of large-scale WSNs have become economically feasible. However, there exist issues such as limited communication and the curse of dimensionality in applying machine-learning algorithms such as support vector regression (SVR) on large-scale WSNs. Here, in order to overcome such issues, we propose an ensemble implementation of SVR for the problem of target localization. The convergence property of the localization algorithm using the ensemble SVR is verified, and the robustness of the proposed scheme against measurement noise is analyzed. Furthermore, experimental results confirm that the estimation performance of the proposed method is more accurate and robust to measurement noise than the conventional SVR predictor.
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