Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Interval prediction for traffic time series using local linear predictor
This paper addresses the issue of the interval forecasting (constructing prediction intervals for future observations) of the traffic data time series using one of local polynomial nonparametric models - the local linear predictor. Two methods are proposed and compared. One is based on the theoretical formulation of the asymptotic prediction intervals and another is an empirical procedure using bootstrap, both for the local linear predictor. Finally, a case study using real-world traffic data is presented for both approaches, along with the results compared with each other. The results coincide with expectations and have validated the proposed methods.
Interval prediction for traffic time series using local linear predictor
This paper addresses the issue of the interval forecasting (constructing prediction intervals for future observations) of the traffic data time series using one of local polynomial nonparametric models - the local linear predictor. Two methods are proposed and compared. One is based on the theoretical formulation of the asymptotic prediction intervals and another is an empirical procedure using bootstrap, both for the local linear predictor. Finally, a case study using real-world traffic data is presented for both approaches, along with the results compared with each other. The results coincide with expectations and have validated the proposed methods.
Interval prediction for traffic time series using local linear predictor
Hongyu Sun, (Autor:in) / Chunming Zhang, (Autor:in) / Bin Ran, (Autor:in)
01.01.2004
421331 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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