Name
Abstract | ||
|---|---|---|
Understanding and forecasting mobility patterns and travel demand are fundamental and critical to efficient transport infrastructure planning and service operation. However, most existing studies focused on deterministic demand estimation/prediction/analytics. Differently, this study provides confidence interval based demand forecasting, which can help transport planning and operation authorities ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TITS.2020.3041234 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | DocType | Volume |
Predictive models,Uncertainty,Convolution,Correlation,Demand forecasting,Bayes methods,Planning | Journal | 23 |
Issue | ISSN | Citations |
5 | 1524-9050 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |