A Combination Prediction Model for Short Term Travel Demand of Urban Taxi
Source abstract
Abstract
This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors. The model... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Transportation Planning and Optimization · Traffic Prediction and Management Techniques · Transportation and Mobility Innovations
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
Show source-provided references
1. Short-term traffic flow prediction of expressway considering spatial influences
2. Short-term traffic prediction based on time series decomposition10.1016/j.physa.2021.126441 ↗
3. An optimal deep learning for cooperative intelligent transportation system
4. An ensemble learning short-term traffic flow forecasting with transient traffic regimes10.4028/www.scientific.net/AMM.97-98.849 ↗
5. Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: Theoretical basis and empirical results10.1061/(ASCE)0733-947X(2003)129:6(664) ↗
6. Three revised kalman filtering models for short-term rail transit passenger flow prediction10.1155/2016/9717582 ↗
7. DeepPF: A deep learning based architecture for metro passenger flow prediction10.1016/j.trc.2019.01.027 ↗
8. Gray markov model in the intersection of short-term traffic flow
9. Short-term passenger flow forecast for urban rail transit based on multi-source data
10. Short-term passenger flow prediction using a bus network graph convolutional long short-term memory neural network model10.1177/03611981221112673 ↗
11. A passenger volume prediction method based on temporal and spatial characteristics for urban rail transit
12. The research of railway passenger flow prediction model based on BP neural network
13. A hybrid deep learning based traffic flow prediction method and its understanding10.1016/j.trc.2018.03.001 ↗
14. Prediction of passenger flow in urban rail transit based on big data analysis and deep learning10.1109/ACCESS.2019.2944744 ↗
15. Predicting station-level short-term passenger flow in a citywide metro network using spatiotemporal graph convolutional neural networks10.3390/ijgi8060243 ↗
16. Attention-based multiple graph convolutional recurrent network for traffic forecasting10.3390/su15064697 ↗
17. Short-term traffic flow prediction: An integrated method of econometrics and hybrid deep learning10.1109/TITS.2021.3052796 ↗
18. Metaheuristic optimization of time series models for predicting networks traffic
19. Dfree-LSTM: An error distribution free deep learning for short-term traffic flow forecasting10.1016/j.neucom.2023.01.009 ↗
20. Deep irregular convolutional residual LSTM for urban traffic passenger flows prediction10.1109/TITS.2019.2900481 ↗
21. Short-term passenger flow forecast of urban rail transit based on PCA-LSTM model
22. A combined method for short-term traffic flow prediction based on recurrent neural network10.1016/j.aej.2020.06.008 ↗
23. Deep spatio-temporal residual networks for citywide crowd flows prediction
24. Short-term traffic flow forecast based on improved wavelet packet and long short-term memory combination model
25. Analysis of prediction accuracy under the selection of optimum time granularity in different metro stations10.3390/su11195281 ↗
26. Short-term forecast of OD passenger flow based on ensemble empirical mode decomposition10.3390/su14148562 ↗
27. Fedstn: Graph representation driven federated learning for edge computing enabled urban traffic flow prediction10.1109/TITS.2022.3157056 ↗
28. Privacy-preserving traffic flow prediction: A federated learning approach10.1109/JIOT.2020.2991401 ↗
29. Study on the improvement of the application of complete ensemble empirical mode decomposition with adaptive noise in hydrology based on RBFNN data extension technology
30. Fine-grained multivariate time series anomaly detection in IoT
31. Physiological time-series analysis using approximate entropy and sample entropy10.1152/ajpheart.2000.278.6.H2039 ↗