Big Spatiotemporal Data Analytics: a research and innovation frontier-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Big Spatiotemporal Data Analytics: a research and innovation frontier

Published:2019-12-02 Issue:6 Volume:34 Page:1075-1088
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Yang Chaowei¹^ORCID,Clarke Keith²^ORCID,Shekhar Shashi³,Tao C. Vincent⁴

Affiliation:

1. NSF Spatiotemporal Innovation Center and Department of Geography and GeoInformation Science, George Mason University, Fairfax, VA, USA,

2. Department of Geography, University of California, Santa Barbara, CA, USA

3. Department of Computer Science, University of Minnesota, Minneapolis, MN, USA

4. Wuhan University and Z Ventures Group, Shanghai, PR China

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2019.1698743

Reference79 articles.

1. Artificial Intelligence in IoT

2. A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

3. Rapid Transit Systems: Smarter Urban Planning Using Big Data, In-Memory Computing, Deep Learning, and GPUs

4. HadoopTrajectory: a Hadoop spatiotemporal data processing extension

5. A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data

Cited by 62 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. Efficient Online Big Data Stream Clustering Using Dual Interactive Wasserstein Generative Adversarial Network;International Journal on Artificial Intelligence Tools;2024-06-12

2. Dynamic measurements of geographical accessibility considering traffic congestion using open data: a cross-sectional assessment for haemodialysis services in Cali, Colombia;The Lancet Regional Health - Americas;2024-06

3. Efficient distributed association management method of data, model, and knowledge for digital twin railway;International Journal of Digital Earth;2024-05-02

4. A Data-Driven Model Selection Approach to Spatio-Temporal Prediction;Lecture Notes in Computer Science;2024

5. How to manage massive spatiotemporal dataset from stationary and non-stationary sensors in commercial DBMS?;Knowledge and Information Systems;2023-11-20

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