Fault Detection in Wireless Sensor Networks through the Random Forest Classifier

Fault Detection in Wireless Sensor Networks through the Random Forest Classifier

Wireless Sensor Networks (WSNs) are vulnerable to faults because of their deployment in unpredictable and hazardous environments. This makes WSN prone to failures such as software, hardware, and communication failures. Due to the sensor’s limited resources and diverse deployment fields, fa...

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Bibliographic Details
Main Authors: Zainib Noshad, Nadeem Javaid, Tanzila Saba, Zahid Wadud, Muhammad Qaiser Saleem, Mohammad Eid Alzahrani, Osama E. Sheta
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Sensors
Subjects:
WSNs
fault detection
machine learning
random forest
support vector machine
convolutional neural network
Online Access:https://www.mdpi.com/1424-8220/19/7/1568

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https://www.mdpi.com/1424-8220/19/7/1568

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