Name
Title | ||
|---|---|---|
A Fast and Resource Efficient Method for Indoor Positioning Using Received Signal Strength. |
Abstract | ||
|---|---|---|
This paper proposes an indoor localization method using online independent support vector machine (OISVM) classification method and undersampling techniques. The system is based on the received signal strength indicator (RSSI) of Wi-Fi signals. A new undersampling algorithm is developed to address the imbalanced data problem associated with the OISVM, and a kernel function parameter selection algo... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TVT.2016.2530761 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Support vector machines,Training,Wireless LAN,Prediction algorithms,Estimation,Training data,Received signal strength indicator | Online learning,Computer science,Support vector machine,Selection algorithm,Undersampling,Electronic engineering,Signal strength,Time complexity,Kernel (statistics) | Journal |
Volume | Issue | ISSN |
65 | 12 | 0018-9545 |
Citations | PageRank | References |
4 | 0.40 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wu Zheng | 1 | 33 | 7.06 |
| Kechang Fu | 2 | 4 | 0.40 |
| Esrafil Jedari | 3 | 42 | 5.81 |
| Shaeera Rabbanee Shuvra | 4 | 4 | 0.40 |
| Rashid Rashidzadeh | 5 | 92 | 15.98 |
| Mehrdad Saif | 6 | 334 | 48.75 |