全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于模糊核c-means算法的位置指纹聚类

, PP. 1180-1184

Keywords: 位置指纹聚类,区间值数据,核方法,模糊c-means

Full-Text   Cite this paper   Add to My Lib

Abstract:

提出一种针对位置指纹的模糊核c-means聚类算法.将位置指纹归结为一种服从正态分布的区间值数据以反映接入点信号强度采样值的不确定性,通过区间中值和大小确定的正态分布函数将位置指纹映射为特征空间中的一点,并在该特征空间中采用基于核方法的模糊c-means算法对其进行聚类.通过ZigBee定位实验表明,该方法对于位置指纹的分类效果明显好于基于信号强度平均值的c-means聚类,可在保证定位精度的前提下有效降低定位的计算量.

References

[1]  Peng Y G, Li Y L, Lu Z C, et al. Method for saving energy in Zigbee network[C]. In: WiCom '09 5th International Conference on Wireless Communications, Networking and Mobile Computing, Beijing, China, 2009. 1-3.
[2]  Chen Y Q, Yang Q, Yin J, et al. Power-efficient access-point selection for indoor location estimation. Knowledge and Data Engineering[J]. IEEE Trans on Knowledge and Data Engineering, 2006, 18(7): 877-888.
[3]  Zhang M H, Zhang S S, CAO J. Probability-based Clustering and Its Application to WLAN Location Estimation[J]. Journal of Shanghai Jiaotong University (Science), 2008, 13(5):547-552.
[4]  Ladd A M, Bekris K E, Rudys A, et al. Robotics-based Location Sensing Using Wireless Ethernet[C]. In Proceedings of the Eighth Annual International Conference on Mobile Computing and Networking (MOBICOM), Atlanta, GA, 2002: 227-238.
[5]  张莉, 周伟达, 焦李成. 核聚类算法[J]. 计算机学报, 2002, 25(6): 587-590.
[6]  曲福恒, 胡雅婷, 马驷良. 基于模拟退火的无监督核模糊聚类算法[J]. 吉林大学学报, 2009, 47(2): 317-322.
[7]  (Qu F H, Hu Y T, Ma S L. Unsupervised Kernel Fuzzy Clustering Algorithm Based on Simulated Annealing[J]. Journal of Jilin University, 2009, 47(2): 317-322.)
[8]  Bahl P, Padmanabhan V N. RADAR: an In-building RF-based Location and Tracking System[C]. In Proceedings of the IEEE INFOCOM, Tel-Aviv, Israel, 2000: 775-784.
[9]  Youssef M, Agrawala A. Location-clustering techniques for energy-efficient WLAN location determination systems[J]. International Journal of Computers and Applications, 2006, 28(3): 278-283.
[10]  Kaemarungsi K, Krishnamurthy, P. Properties of indoor received signal strength for WLAN location fingerprinting [C]. Proceedings of 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, Boston, USA, 2004: 14-23.
[11]  (Zhang L, Zhou W D, Jiao L C. Kernel Clustering Algorithm[J]. Chinese Journal of Computers, 2002, 25(6): 587-590.)
[12]  伍忠东, 高新波, 谢维信. 基于核方法的模糊聚类算法[J]. 西安电子科技大学学报, 2004, 31(4): 533-537.
[13]  (Wu Z D, Gao X B, Xie W X. A study of a new fuzzy clustering algorithm based on the kernel method[J]. Journal of Xidian University, 2004, 31(4): 533-537.)
[14]  储岳中. 一类基于高斯核的动态聚类算法研究[J]. 华中科技大学学报, 2009, 37(8): 43-45.
[15]  (Chu Y Z. Gaussian kernel-based dynamic clustering algorithm[J]. Journal of Huazhong University of Science and Technology, 2009, 37(8): 43-45.)

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133