A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…One aspect is malicious traffic identification in Vehicular networks. We proposed a hybrid approach uses automated feature engineering via correlation-based feature selection (CFS) and principal component analysis (PCA)-based dimensionality reduction to reduce feature matrix size before a series of dense layers are used for classification. …”
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ANTi-JAM solutions for smart roads: Ant-inspired traffic flow rules under CAVs environment by Marco Guerrieri, Nicola Pugno

“…During their movement, ants generate trail networks that share many characteristics with vehicular traffic on highways. This research aims to estimate the values of traffic flow variables (mean speed, density, and flow) in ant trails without intersections or branches that could alter the dynamics of each ant. …”
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