Fuzzy support vector machines for device-free localization

Yi Yuan Chiang, Wang Hsin Hsu, Sheng Cheng Yeh, Yi Chen Li, Jung Shyr Wu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

10 引文 斯高帕斯(Scopus)

摘要

In this paper, we develop a novel fuzzy support vector machine for device-free localization. The fuzzy support vector machine is an integration of support vector machines (SVMs) and fuzzy systems; therefore a fuzzy system can be extracted from an SVM. We not only show how to integrate SVMs and fuzzy systems, but also show how to reduce the complexity of the obtained fuzzy systems. One major benefit of reducing the complexity of fuzzy systems is that the obtained fuzzy systems are easy to be optimized. The proposed method is proved to be effective through experimental studies, which is carried in a badminton court in which four WiFi access points and 17 test points are deployed. The simulation results show the reduced fuzzy system is easy to perform optimization and generates better results than pure SVM. An simulation result shows the correctness of pure SVM is 66.8% and the correctness of optimized fuzzy systems is 74.6%.

原文???core.languages.en_GB???
主出版物標題2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings
頁面2169-2172
頁數4
DOIs
出版狀態已出版 - 2012
事件2012 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2012 - Graz, Austria
持續時間: 13 5月 201216 5月 2012

出版系列

名字2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???2012 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2012
國家/地區Austria
城市Graz
期間13/05/1216/05/12

指紋

深入研究「Fuzzy support vector machines for device-free localization」主題。共同形成了獨特的指紋。

引用此