1
Bannari Amman Institute of Technology, Sathyamangalam, Erode
2
PSG College of Technology, Coimbatore
Abstract
Because of the recent advancement in the technologies like Internet of things and Artificial Intelligence, most of the industries have adapted into automation. In our routine life most of the devices have become automated one with the help of more connectivity and flawless integration of information technology. Most of the modern vehicles are equipped with smart technologies with security concepts. To identify the abnormality in vehicle network, an anomaly detection mechanism is proposed in this paper. By using this anomaly detection system we are able distinguish the vehicular attacks in the networks and also able to detect the manufacturing defects for ensuring the quality assurance. Due his paper describes a deep learning based neural network model that will explore the abnormalities in the vehicular network data. Various steps in the neural network implementation part have been illustrated. It also evaluates the experimental results by applying the deep learning method on the given real-time data. Due to the immediate responsiveness of the system, it has been gaining much more attention in the automobile industry.
K, G., V, D., & V, K. (2021). Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry. Int. J. of Aquatic Science, 12(3), 1712-1717.
MLA
Ganagavalli K; Dr.Santhi. V; Krishnamoorthy V. "Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry". Int. J. of Aquatic Science, 12, 3, 2021, 1712-1717.
HARVARD
K, G., V, D., V, K. (2021). 'Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry', Int. J. of Aquatic Science, 12(3), pp. 1712-1717.
VANCOUVER
K, G., V, D., V, K. Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry. Int. J. of Aquatic Science, 2021; 12(3): 1712-1717.
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