Kourosh Noori

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In this paper, a fuzzy Bayesian traction control system was developed for rail vehicles with speed sensors in intelligent transportation systems. The system included three main components to sense, process, and classify the traction conditions. The information received from the speed sensors is used to avoid any error that might cause service interruption(More)
In this paper, a real-time intelligent traction control model for speed sensor vehicles in computer-based transit systems is proposed. Using the Bayesian decision theory, the model analyzes speed sensor data to learn and classify the train traction conditions (i.e., spin/slip, normal, and slide) that are required for studying vehicle motion patterns. The(More)
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