基于Elman神经网络的无线传感器网络测距模型

doi:10.3976/j.issn.1002-4026.2011.06.023

Shandong Science ›› 2011, Vol. 24 ›› Issue (6): 92-95.doi: 10.3976/j.issn.1002-4026.2011.06.023

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An Elman neural networks based ranging model for wireless sensor networks

HAN Qing-Yu¹, LI Yuan², GONG Hong-Cai¹, GUO Qiang¹

1.School of Information Management, Shandong University of Finance and Economics, Jinan 250014, China； 2.School of Accounting, Shandong University of Finance and Economics, Jinan 250014, China

Received:2011-07-12 Published:2011-12-20 Online:2011-12-20

Abstract

Abstract:

We collect the received signal strength values of a node at different positions in a wireless sensor network. We then employ Elman neural networks to construct a mapping model relationship between received signal strength and radio wave propagation path distance. We therefore can train such neural networks with the collected signal strength before detect distance with the well trained neural networks. Experimental results show that this approach has better ranging capability.

Key words: Elman neural networks, wireless sensor networks, ranging model

CLC Number:

TP312

HAN Qing-Yu, LI Yuan, GONG Hong-Cai, GUO Qiang. An Elman neural networks based ranging model for wireless sensor networks[J].Shandong Science, 2011, 24(6): 92-95.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits third parties to freely share (i.e., copy and redistribute the material in any medium or format) and adapt (i.e., remix, transform, or build upon the material) the articles published in this journal, provided that appropriate credit is given, a link to the license is provided, and any changes made are indicated. The material may not be used for commercial purposes. For details of the CC BY-NC 4.0 license, please visit: https://creativecommons.org/licenses/by-nc/4.0

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An Elman neural networks based ranging model for wireless sensor networks

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