Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting حسب Abdelkader Baggag (16864140)

"…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …"

CEAP حسب Abdel Wahab, Omar

"…The basic idea is to launch cooperative monitoring between vehicles to build a training dataset that is analyzed by the Support Vector Machine (SVM) learning technique in online and incremental fashions to classify the smart vehicles either cooperative or malicious. …"
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