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Mobile nodes localisation based on hill climbing optimisation

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成果类型:
期刊论文
作者:
Wenjie Hu;Yao Chen;Jincai Yang(杨进才);Xianjun Shen
通讯作者:
Shen, Xianjun(xjshen@mail.ccnu.edu.cn)
作者机构:
[Wenjie Hu] College of Information Engineering, Xianning Vocational Technical College, Xianning, Hubei, China
[Jincai Yang; Yao Chen; Xianjun Shen] School of Computer, Central China Normal University, Wuhan, Hubei, China
Collaborative & Innovative Center for Educational Technology, Central China Normal University, Wuhan, Hubei, China
[Xianjun Shen] Collaborative and Innovative Center for Educational Technology, Central China Normal University, Wuhan, Hubei, China
通讯机构:
School of Computer, Central China Normal University, Wuhan, Hubei, China
语种:
英文
关键词:
Monte Carlo methods;Sensor nodes;Wireless sensor networks;Hill climbing;Localisation;MCL algorithm;Mobile nodes;Optimisations;Particle swarm optimisation;Positioning accuracy;Sampling rates;Particle swarm optimization (PSO)
期刊:
International Journal of Wireless and Mobile Computing
ISSN:
1741-1084
年:
2016
卷:
11
期:
1
页码:
18-23
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
Aiming at the critical drawbacks of low sampling rate and less accuracy in Monte Carlo Localisation (MCL) algorithm, a novel mobile nodes localisation algorithm based on the hill climbing optimisation strategy is proposed, namely HCPSO-MCL (Hill Climbing Particle Swarm Optimisation-MCL). The HCPSO-MCL algorithm combines the hill climbing strategy and particle swarm optimisation to correct the location estimated by the MCL algorithm, which results in effective implementation and accurate positioning of the mobile nodes. The experimental results ...

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