Все выпуски
- 2024 Том 16
- 2023 Том 15
- 2022 Том 14
- 2021 Том 13
- 2020 Том 12
- 2019 Том 11
- 2018 Том 10
- 2017 Том 9
- 2016 Том 8
- 2015 Том 7
- 2014 Том 6
- 2013 Том 5
- 2012 Том 4
- 2011 Том 3
- 2010 Том 2
- 2009 Том 1
Использование сверточных нейронных сетей для прогнозирования скоростей транспортного потока на дорожном графе
Список литературы:
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. — 2015. — Software available from tensorflow.org. , , , et al.
- Analysis of freeway traffic time-series data by using Box – Jenkins techniques // Transportation Research Record. — 1979. — no. 722. — P. 116. , .
- Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks. — 2015. — no. jun. — P. 1–9. , , , et al.
- Caltrans Performance Measurement. — State of California. — http://pems.dot.ca.gov/.
- Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions // Expert Systems with Applications. — 2009. — V. 36, no. 3. — P. 6164–6173. — Part 2. — DOI: 10.1016/j.eswa.2008.07.069. , , , et al.
- Learning Deep Representation from Big and Heterogeneous Data for Traffic Accident Inference / Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16). — 2016. — P. 338–344. , , , et al.
- Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. — 2014. , , , et al.
- Nonparametric regression and short-term freeway traffic forecasting. — 1991. — V. 117, no. 2. — P. 178–188. , .
- Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. — 2016. — no. Nips. , , .
- LSTM: A Search Space Odyssey // IEEE Transactions on Neural Networks and Learning Systems. — 2017. — V. 28, no. 10. — P. 2222–2232. — DOI: 10.1109/TNNLS.2016.2582924. — MathSciNet: MR3709742. , , , et al.
- Long Short-Term Memory // Neural Computation. — 1997. — V. 9, no. 8. — P. 1735–1780. — DOI: 10.1162/neco.1997.9.8.1735. , .
- Deep architecture for traffic flow prediction: Deep belief networks with multitask learning // IEEE Transactions on Intelligent Transportation Systems. — 2014. — V. 15, no. 5. — P. 2191–2201. — DOI: 10.1109/TITS.2014.2311123. , , , et al.
- Research of Traffic Flow Forecasting Based on Neural Network // 2008 Second International Symposium on Intelligent Information Technology Application. — 2008. — V. 2, no. 973. — P. 451–456. , .
- Residual LSTM: Design of a deep recurrent architecture for distant speech recognition / Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. — 2017. — V. 2017, no. Augus. — P. 1591–1595. , , .
- Adam: A Method for Stochastic Optimization. — 2015. — P. 1–15. , .
- Semi-Supervised Classification with Graph Convolutional Networks / International Conference on Learning Representations (ICLR). — 2017. , .
- Gradient-based learning applied to document recognition // Proceedings of the IEEE. — 1998. — V. 86, no. 11. — P. 2278–2323. — DOI: 10.1109/5.726791. , , , et al.
- Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN. — 2018. — no. 1. , , , et al.
- Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecating. — 2017. — P. 1–12. , , , et al.
- On Kinematic Waves. II. A Theory of Traffic Flow on Long Crowded Roads // Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. — 1955. — V. 229, no. 1178. — P. 317–345. — DOI: 10.1098/rspa.1955.0089. — MathSciNet: MR0072606. , .
- Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning // IEEE Transactions on Intelligent Transportation Systems. — 2013. — V. 14, no. 2. — P. 871–882. — DOI: 10.1109/TITS.2013.2247040. , , .
- Traffic Flow Prediction with Big Data: A Deep Learning Approach // IEEE Transactions on Intelligent Transportation Systems. — 2015. — V. 16, no. 2. — P. 865–873. — MathSciNet: MR3337615. , , , et al.
- Shock Waves on the Highway // Operations Research. — 1956. — V. 4, no. 1. — P. 42–51. — DOI: 10.1287/opre.4.1.42. — MathSciNet: MR0075522. .
- Structured Sequence Modeling with Graph Convolutional Recurrent Networks. — 2016. — no. 2013. — P. 1–10. , , , et al.
- Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. — 2015. — P. 1–12. , , , et al.
- Sequence to Sequence Learning with Neural Networks. — 2014. — P. 1–9. , , .
- Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results // Journal of Transportation Engineering. — 2003. — V. 129, no. 6. — P. 664–672. , .
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