Predicting citywide crowd flows using deep spatio-temporal residual networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Predicting citywide crowd flows using deep spatio-temporal residual networks

Published:2018-06 Issue: Volume:259 Page:147-166
ISSN:0004-3702
Container-title:Artificial Intelligence
language:en
Short-container-title:Artificial Intelligence

Author:

Zhang Junbo,Zheng Yu,Qi Dekang,Li Ruiyuan,Yi Xiuwen,Li Tianrui

Funder

National Natural Science Foundation of China

China National Basic Research Program

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference51 articles.

1. Deep spatio-temporal residual networks for citywide crowd flows prediction;Zhang,2017

2. Urban computing: concepts, methodologies, and applications;Zheng;ACM Trans. Intell. Syst. Technol.,2014

3. DNN-based prediction model for spatio-temporal data;Zhang,2016

4. Deep learning;LeCun;Nature,2015

5. Efficient backprop;LeCun,2012

Cited by 367 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. Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook;Information Fusion;2025-01

2. Adaptive graph neural network for traffic flow prediction considering time variation;Expert Systems with Applications;2024-12

3. STVANet: A spatio-temporal visual attention framework with large kernel attention mechanism for citywide traffic dynamics prediction;Expert Systems with Applications;2024-11

4. A Hybrid Traffic Flow Forecasting and Risk-Averse Decision Strategy for Hydrogen-Based Integrated Traffic and Power Networks;IEEE Systems Journal;2024-09

5. Regularized Spatial–Temporal Graph Convolutional Networks for Metro Passenger Flow Prediction;IEEE Transactions on Intelligent Transportation Systems;2024-09

同舟云学术

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