Name
Title | ||
|---|---|---|
Using an ARIMA-GARCH Modeling Approach to Improve Subway Short-Term Ridership Forecasting Accounting for Dynamic Volatility. |
Abstract | ||
|---|---|---|
Subway short-term ridership forecasting plays an important role in intelligent transportation systems. However, limited efforts have been made to forecast the subway short-term ridership, accounting for dynamic volatility. The traditional forecasting methods can only provide point values that are unable to offer enough information on the volatility/uncertainty of the forecasting results. To fill t... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TITS.2017.2711046 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Forecasting,Predictive models,Public transportation,Reliability,Time series analysis,Mathematical model,Analytical models | Econometrics,Accounting,Time series,Simulation,Autoregressive integrated moving average,Prediction interval,Engineering,Intelligent transportation system,Autoregressive conditional heteroskedasticity,Coverage probability,Volatility (finance),Beijing | Journal |
Volume | Issue | ISSN |
19 | 4 | 1524-9050 |
Citations | PageRank | References |
6 | 0.52 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chuan Ding | 1 | 12 | 1.34 |
| Jinxiao Duan | 2 | 6 | 0.52 |
| Yanru Zhang | 3 | 15 | 1.57 |
| Xinkai Wu | 4 | 7 | 1.89 |
| Guizhen Yu | 5 | 49 | 11.52 |