Anomaly Detection in Critical Infrastructure Using Probabilistic Neural Network

2019 ◽  
pp. 129-141 ◽  
Author(s):  
M. R. Gauthama Raman ◽  
Nivethitha Somu ◽  
Aditya P. Mathur
Keyword(s):  
Neural Network ◽  
Anomaly Detection ◽  
Critical Infrastructure ◽  
Probabilistic Neural Network

scholarly journals A Probabilistic Neural Network with Anomaly Detection and Related Application to an EMG-controlled Prosthetic Hand

2015 ◽  
Vol 33 (4) ◽  
pp. 275-284
Author(s):  
Keisuke Shima ◽  
Junichi Imagi ◽  
Hideaki Hayashi ◽  
Taro Shibanoki ◽  
Yuichi Kurita ◽  
...  
Keyword(s):  
Neural Network ◽  
Anomaly Detection ◽  
Probabilistic Neural Network ◽  
Prosthetic Hand ◽  
Related Application

Classification and Identification of Power System Disturbances Using Wavalet and Artificial Neural Network Technique

2005 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
Noraliza Hamzah ◽  
Wan Nor Ainin Wan Abdullah ◽  
Pauziah Mohd Arsad
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Probabilistic Neural Network ◽  
Microsoft Excel ◽  
Waveform Data ◽  
The Neural Network ◽  
Harmonic Voltage ◽  
Power Quality Disturbances ◽  
Electronic Load ◽  
Wavelet Technique

Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code.  Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification.

A neural network approach to anomaly detection in spectra

1997 ◽  
Author(s):  
Daniel Benzing ◽  
Kevin Whitaker ◽  
Dedra Moore ◽  
Daniel Benzing ◽  
Kevin Whitaker ◽  
...  
Keyword(s):  
Neural Network ◽  
Anomaly Detection ◽  
Network Approach ◽  
Neural Network Approach

Graph Neural Network Approach for Anomaly Detection

Measurement ◽  
2021 ◽  
pp. 109546
Author(s):  
Lingqiang Xie ◽  
Dechang Pi ◽  
Xiangyan Zhang ◽  
Junfu Chen ◽  
Yi Luo ◽  
...  
Keyword(s):  
Neural Network ◽  
Anomaly Detection ◽  
Network Approach ◽  
Neural Network Approach
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