Please use this identifier to cite or link to this item:
http://dspace.uniten.edu.my/jspui/handle/123456789/7186| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yuen, C.W. | en_US |
| dc.contributor.author | Balasubramaniam, N. | en_US |
| dc.contributor.author | Din, N.Md. | en_US |
| dc.date.accessioned | 2018-01-11T09:11:06Z | - |
| dc.date.available | 2018-01-11T09:11:06Z | - |
| dc.date.issued | 2009 | - |
| dc.description.abstract | This paper proposes to improve the performance of the K-Nearest Neighbour algorithm in predicting the location of a mobile user in an indoor environment. Emphasis is placed on RSS sample vector fluctuation stabilization, resulting in an overall 12% increase in the precision of predicting correct locations compared to previous efforts. ©2009 IEEE. | |
| dc.language.iso | en | en_US |
| dc.title | Improvement of indoor location sensing algorithm using Wireless Local Area Network (WLAN) IEEE 802.11b | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.doi | 10.1109/MICC.2009.5431451 | - |
| item.fulltext | No Fulltext | - |
| item.grantfulltext | none | - |
| Appears in Collections: | COGS Scholarly Publication | |
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