基于Mamdani型模糊推理的加权质心定位算法

计算机科学 ›› 2015, Vol. 42 ›› Issue (10): 101-105.

基于Mamdani型模糊推理的加权质心定位算法

王万良,石浩,李燕君

浙江工业大学计算机科学与技术学院杭州310023,浙江工业大学计算机科学与技术学院杭州310023,浙江工业大学计算机科学与技术学院杭州310023

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受“十二五”国家科技支撑计划(2012BAD10B01)资助

Weighted Centroid Localization Algorithm Based on Mamdani Fuzzy Theory

WANG Wan-liang, SHI Hao and LI Yan-jun

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 为了提高加权质心定位算法在室内环境中的定位精度,提出使用实际环境中的RSS数据通过蝙蝠算法拟合输入隶属度函数,通过Mamdani型模糊推理获得节点间精确的权值,以提高加权质心定位算法的定位精度。在Zigbee平台上实现了该算法,通过实验比较3种不同的质心定位算法,结果表明:Mamdani型模糊推理因采用经过蝙蝠算法优化的隶属度函数而具有更小的平均定位误差。

关键词: 加权质心定位算法,模糊推理,蝙蝠算法,接收信号强度

Abstract: In many cases of wireless sensor networks application,the accuracy of weighted centroid localization algorithm depends on the precision of weight.In this paper,Mamdani fuzzy logic inference approach with improved RSS membership function based on bat algorithm was proposed to improve the accuracy of weighted centroid localization algorithm.With applying Zigbee hardware platform to compare three types of centroid algorithms,it draws a conclusion that the desired accuracy in door localization can be achieved with optimized RSS membership function by bat algorithm.

Key words: Weighted centroid localization algorithm,Fuzzy logic,Bat algorithm,Received signal strength

王万良,石浩,李燕君. 基于Mamdani型模糊推理的加权质心定位算法[J]. 计算机科学, 2015, 42(10): 101-105. https://doi.org/

WANG Wan-liang, SHI Hao and LI Yan-jun. Weighted Centroid Localization Algorithm Based on Mamdani Fuzzy Theory[J]. Computer Science, 2015, 42(10): 101-105. https://doi.org/

参考文献

[1] Qiao D P,Grantham K H.Evolutionary approach on connectivity-based sensor network localization [J].Applied Soft Computing,2014,22:36-46
[2] Larios D F,Barbancho J,Molina F J,et al.Localization based on an intelligent distributed fuzzy system applied to WSN [J].Ad Hoc Networks,2012,5(10):604-622
[3] Chen C C,Lin T C.A Low-Cost Anchor Placement Strategy for Range-Free Localization Problems in Wireless Sensor Networks [J].International Journal of Distributed Sensor Networks,2013,2(3):23-30
[4] Wang S S,Shih K P,Chang C Y.Distributed direction-based localization in wireless sensor networks [J].Computer Communications,2007,30(6):1424-1439
[5] Nirupama B,Heidemann J, Deborah E.GPS-less low cost outdoor localization for very small devices[J].IEEE Personal Communications,2000,7(5):28-34
[6] Gui L Q,Thierry V,Wei A,et al.Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks [J].Ad Hoc Networks,2014,4(8):1-19
[7] Feng C X,Liu Z.A New Node Self-Localization AlgorithmBased RSSI for Wireless Sensor Networks[C]∥Proceedings of the Fifth Computational and Information Sciences(ICCIS).2013:1616-1619
[8] Shon M,Jo M,Choo H.An interactive cluster-based MDS localization scheme for multimedia information in wireless sensor networks [J].Computer Communications,2012,5(15):1921-1929
[9] 郜丽鹏,朱梅冬,杨丹.基于ZigBee的加权质心定位算法的仿真与实现[J].传感技术学报,2010,23(1):149-152 Gao Li-peng,Zhu Mei-dong,Yang Dan.Simulation and Implement of Weighted Centroid Localization Algorithm Based on ZigBee [J].Chinese Journal of Sensors and Actuators,2010,23(1):149-152
[10] 李牧东,熊伟,郭龙.基于人工蜂群算法的DV-Hop定位改进算法[J].计算机科学,2013,40(1):33-36 Li Mu-dong,Xiong Wei,Guo Long.Improvement of DV-Hop Localization Algorithm Based on Artificial Bee Colony Algorithm [J].Computer Science,2013,40(1):33-36
[11] 韩东升,杨维,刘洋,等.煤矿井下基于RSSI的加权质心定位算法[J].煤炭学报,2013,3(38):522-528 Han Dong-sheng,Yang Wei,Liu Yang,et al.A Weighted Centroid Localization Algorithm Based on Received Signal Strength indicator for Underground Coal Mine [J].Journal of China Coal Society,2013,3(38):522-528
[12] Kumar A,Chand N,Kumar V,et al.Range Free LocalizationSchemes for Wireless Sensor Networks[J].International Journal of Computer Networks & Communications (IJCNC),2011,3(6):132-144
[13] Proakis J,Salehi M.Digital Communications [M].New York:McGraw-Hill Press,2010:165-170
[14] Yang X S.A New Metaheuristic Bat-Inspired Algorithm[C]∥Nature Inspired Cooperative Strategies for Optimization (NISCO 2010).Studies in Computational Intelligence,Springer Berlin,2010:65-74
[15] Skulavik T,Kopcek M,Mydlo P,et al.The defuzzification me-thods influence on fuzzy control of nuclear reactor[C]∥Procee-ding of International Symposium on Computational and Business Intelligence ISCBI 2013).New Delhi:IEEE Press,2013:119-122
[16] Mitsuishi T.Continuity of Approximate Reasoning Using Center of Sums Defuzzification Method [C]∥Proceedings of the 35th International Convention on Information and Communication Technology,Electronics and Microelectronics (MIPRO).Opatija:IEEE Press,2013:991-994
[17] Arabacioglu B C.Using fuzzy inference system for architectural space analysis [J].Applied Soft Computing,2009,10(3):926-937

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