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US09390622B2 Performing-time-series based predictions with projection thresholds using secondary time-series-based information stream 有权
基于执行时间序列的预测与投影阈值使用基于次级时间序列的信息流

Performing-time-series based predictions with projection thresholds using secondary time-series-based information stream
Abstract:
A prediction modeling system, method and computer program product for implementing forecasting models that involve numerous measurement locations, e.g., urban occupancy traffic data. The method invokes 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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