Masterclass Certificate in Smart City Traffic Data Modeling Techniques
-- ViewingNowThe Masterclass Certificate in Smart City Traffic Data Modeling Techniques is a comprehensive course designed to equip learners with essential skills for navigating the rapidly evolving urban mobility landscape. This course is vital for professionals seeking to stay updated on cutting-edge data modeling techniques that can help optimize traffic management and reduce congestion in smart cities.
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โข Introduction to Smart Cities ← defines the concept of smart cities, their benefits, and the role of traffic data modeling techniques. โข Traffic Data Collection Methods ← covers various data collection methods, including manual counting, sensors, video detection, GPS, and Bluetooth. โข Data Preprocessing Techniques ← discusses data cleaning, normalization, transformation, and aggregation techniques. โข Traffic Flow Theory ← explains fundamental traffic flow concepts, such as speed-flow relationships, capacity, and queueing. โข Traffic Simulation Tools ← introduces microscopic and macroscopic traffic simulation tools, such as VISSIM, SimTraffic, and Paramics. โข Machine Learning Techniques for Traffic Data Modeling ← covers regression, time series, and neural network models for traffic prediction. โข Real-time Traffic Monitoring ← discusses real-time traffic monitoring techniques, including floating car data, probe vehicles, and loop detectors. โข Intelligent Transportation Systems ← introduces ITS technologies, such as adaptive signal control, ramp metering, and traffic responsive systems. โข Traffic Data Visualization ← explains how to present traffic data through maps, charts, and graphs, using tools such as Tableau, Power BI, and QlikView. โข Evaluation Metrics for Traffic Data Modeling ← covers various metrics, such as root mean square error, mean absolute percentage error, and coefficient of determination, for evaluating the performance of traffic data models.
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