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Fault diagnosis of node in wireless sensor network based on the interval-numbers rough neural network

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2 Author(s)
Zhu Hai-Yang ; Sch. of Autom., Univ. of Electron. Sci. & Technol. of China, Chengdu, China ; Lei Lin

This paper proposed a new fault diagnosis method of node in WSN based on the interval-numbers rough neural network. Firstly, this method established the most simple decision-making table of the fault diagnosis by the improved discriminate matrix, then applied rough decision-making analysis method constructed a interval-value information decision-making system of WSN node, and constructed the rough neuron of the input layer; Finally, constructed the fault diagnosis system based on the three-layers feed-forward rough neural network with the interval numbers. The simulation results show that this method made the rate of diagnostic accuracy to 99.24% when the computing time was greatly reduced, and it has high practical value.

Published in:

Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on

Date of Conference:

16-18 April 2010

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