Detection and identification of seismic signals recorded at Krakatau volcano (Indonesia) using artificial neural networks

2008 ◽  
Vol 176 (4) ◽  
pp. 448-456 ◽  
Author(s):  
M. Ibs-von Seht
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Seismic Signals ◽  
Detection And Identification ◽  
Artificial Neural ◽  
Krakatau Volcano

scholarly journals Multiclass decomposition and Artificial Neural Networks for intrusion detection and identification in Internet of Things environments

2021 ◽  
Author(s):  
Cristiano Antonio de Souza ◽  
João Vitor Cardoso ◽  
Carlos Becker Westphall
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Internet Of Things ◽  
False Positives ◽  
Machine Learning Techniques ◽  
Detection And Identification ◽  
Learning Techniques ◽  
Artificial Neural ◽  
Stage Analysis ◽  
The Internet Of Things

The Internet of Things (IoT) systems have limited resources, making it difficult to implement some security mechanisms. It is important to detect attacks against these environments and identify their type. However, existing multi-class detection approaches present difficulties related to false positives and detection of less common attacks. Thus, this work proposes an approach with a two-stage analysis architecture based on One-Vs-All (OVA) and Artificial Neural Networks (ANN) to detect and identify intrusions in fog and IoT computing environments. The results of experiments with the Bot-IoT dataset demonstrate that the approach achieved promising results and reduced the number of false positives compared to state-of-the-art approaches and machine learning techniques.

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

2018 ◽  
pp. 6-11
Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Space Exploration ◽  
Artificial Neural
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