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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2018

15.01.2018

The Failure Detection Method of WSN Based on PCA-BDA and Fuzzy Neural Network

verfasst von: Bing Xu, Xiaoping Zhang, Liqun Liu

Erschienen in: Wireless Personal Communications | Ausgabe 2/2018

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Abstract

The Failure Detection algorithm based on Fuzzy Neural Network (FDD-FNN) method is proposed for effective detection of Wireless Sensor Network (WSN) system failures. In this method, the failure detection method for WSN and the minimum deviation optimization model based on the principle component analysis-Bayes discriminant analysis (PCA-BDA) and feature information entropy are proposed, input layer, fuzzy layer, fuzzy rule layer and ambiguity layer are designed, and the algorithm processes is introduced. Finally, the effects of key factors of FDD-FNN were investigated using simulations and its performance was compared with those of conventional algorithms. The results indicated excellent adaptability of FDD-FNN.
Vorheriger Artikel Development and Application of Artificial Neural Network
Nächster Artikel Bearing Fault Diagnosis Using Multiclass Self-Adaptive Support Vector Classifiers Based on CEEMD–SVD

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Metadaten
Titel
The Failure Detection Method of WSN Based on PCA-BDA and Fuzzy Neural Network
verfasst von
Bing Xu
Xiaoping Zhang
Liqun Liu
Publikationsdatum
15.01.2018
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2018
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-017-5225-9

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