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Performing-time-series based predictions with projection thresholds using secondary time-series-based information stream
Performing-time-series based predictions with projection thresholds using secondary time-series-based information stream
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机译：使用次要的基于时间序列的信息流，使用投影阈值执行基于时间序列的预测
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摘要
A prediction modeling system and computer program product for implementing forecasting models that involve numerous measurement locations, e.g., urban occupancy traffic data. The system a data volatility reduction technique based on computing a congestion threshold for each prediction location, and using that threshold in a filtering scheme. Through the use of calibration, and by obtaining an extremal or other specified solution (e.g., maximization) of empirical volume-occupancy curves as a function of the occupancy level, significant accuracy gains are achieved and at virtually no loss of important information to the end user. The calibration use quantile regression to deal with the asymmetry and scatter of the empirical data. The argmax of each empirical function is used in a unidimensional projection to essentially filter all fully congested occupancy level and treat them as a single state.
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