计算机工程与应用2017，Vol.53Issue(9)：111-116,157,7.DOI:10.3778/j.issn.1002-8331.1511-0185
基于RSOPNN的无线传感器网络节点故障诊断算法
Fault diagnosis of node in WSN based on RSOPNN algorithm
摘要
Abstract
In light of redundant data, noisy data and data reliability existing in fault diagnosis of node in wireless sensor network, this paper proposes a fault diagnosis algorithm(RSOPNN)of wireless sensor network nodes based on the Rough Set theory and Optimized Probabilistic Neural Network. The method uses rough set theory to get reductions of fault diag-nosis from the collection of samples'properties, so that it can decrease the impact of redundant attributes, noisy data on fault diagnosis, and save energy. Then, it chooses the best reduction from multiple reductions above by using the correla-tion between properties of reduction instead of subjective choice to solve the irrationality of subjective choice. Finally, the method reconstructs the fault samples with the best reduction of fault diagnosis as the input of the optimized probabilistic neural network, builds classification model to diagnose faults. Experimental results show that in the case of different data reliabilities, the RSOPNN proposed in this paper can eliminate redundant and noisy data in the original data effectively with higher diagnosis rate, which meets the demand of wireless sensor network.关键词
无线传感器网络/可辨识矩阵/属性约简/概率神经网络/故障诊断Key words
wireless sensor network/discernibility matrix/attribute reduction/probabilistic neural network/fault diagnosis分类
信息技术与安全科学引用本文复制引用
李洋,高岭,孙骞,付志耀..基于RSOPNN的无线传感器网络节点故障诊断算法[J].计算机工程与应用,2017,53(9):111-116,157,7.基金项目
国家科技支撑计划课题(No.2013BAK01B02) （No.2013BAK01B02）
国家自然科学基金(No.61373176) （No.61373176）
陕西省重大科技创新专项资金项目(No.2012ZKC05-2). （No.2012ZKC05-2）
