Traffic flow prediction in inland waterways of Assam region using uncertain spatiotemporal correlative features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geophysics
Link
https://link.springer.com/content/pdf/10.1007/s11600-022-00875-8.pdf
Reference27 articles.
1. Bengio Y, Simard P, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157–166. https://doi.org/10.1109/72.279181
2. Gu Y, Lu W, Xu X, Qin L, Shao Z, Zhang H (2020) An improved Bayesian combination model for short-term traffic prediction with deep learning. IEEE Trans Intell Transp Syst 21(3):1332–1342. https://doi.org/10.1109/tits.2019.2939290
3. Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504–507. https://doi.org/10.1126/science.1127647
4. Hinton GE, Osindero S, Teh Y-W (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527–1554. https://doi.org/10.1162/neco.2006.18.7.1527
5. Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780. https://doi.org/10.1162/neco.1997.9.8.1735
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The nonlinear impact of climate change on inland waterway transportation in the Upper Mississippi—Illinois River Region;Environmental Research: Infrastructure and Sustainability;2024-07-09
2. Incorporating environmental knowledge embedding and spatial-temporal graph attention networks for inland vessel traffic flow prediction;Engineering Applications of Artificial Intelligence;2024-07
3. Research on ship traffic flow prediction based on GTO-CNN-LSTM;Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023);2024-02-20
4. EGFormer: An Enhanced Transformer Model with Efficient Attention Mechanism for Traffic Flow Forecasting;Vehicles;2024-01-06
5. Short-term traffic flow prediction based on optimized deep learning neural network: PSO-Bi-LSTM;Physica A: Statistical Mechanics and its Applications;2023-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3