Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Xu Yuanchang"'
The objective of this study is to develop and test a novel structured deep-learning modeling framework for urban flood nowcasting by integrating physics-based and human-sensed features. We present a new computational modeling framework including an a
Externí odkaz:
http://arxiv.org/abs/2111.08450
Autor:
Yuan, Faxi, Mobley, William, Farahmand, Hamed, Xu, Yuanchang, Blessing, Russell, Dong, Shangjia, Mostafavi, Ali, Brody, Samuel D.
The objective of this study is to predict road flooding risks based on topographic, hydrologic, and temporal precipitation features using machine learning models. Predictive flood monitoring of road network flooding status plays an essential role in
Externí odkaz:
http://arxiv.org/abs/2108.13265
The objective of this study is to predict the near-future flooding status of road segments based on their own and adjacent road segments current status through the use of deep learning framework on fine-grained traffic data. Predictive flood monitori
Externí odkaz:
http://arxiv.org/abs/2104.02276
Publikováno v:
In Computers, Environment and Urban Systems October 2022 97
Akademický článek
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Autor:
Farahmand, Hamed1 (AUTHOR) hamedfarahmand@tamu.edu, Xu, Yuanchang2 (AUTHOR), Mostafavi, Ali1 (AUTHOR)
Publikováno v:
Scientific Reports. 4/25/2023, Vol. 13 Issue 1, p1-15. 15p.
Publikováno v:
Stereotactic & Functional Neurosurgery; 1995, Vol. 65 Issue 1-4, p47-53, 7p
Autor:
Jiang Ji-yu, Xu Yuanchang
Publikováno v:
Agriculture and Agricultural Science Procedia. :163-169
China is one of the most suffering countries in agriculture by Nature. The current statistics shows a growing lose by agriculture risk. Insurance, as a lack part in the agricultural risk management, is constraining the ability to defense the risk and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f57eb48437b622e40feffb1ccd3e5fc
Autor:
Yao R; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China., Lin J; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China., Liu K; The Beijing Municipal Key Laboratory of New Energy Materials and Technologies, School of Materials Sciences and Engineering, University of Science and Technology Beijing, Beijing 100083, China., Xu Y; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China., Xiao B; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China., Zhao J; The Beijing Municipal Key Laboratory of New Energy Materials and Technologies, School of Materials Sciences and Engineering, University of Science and Technology Beijing, Beijing 100083, China., Guo Z; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China., Liu Q; The Beijing Municipal Key Laboratory of New Energy Materials and Technologies, School of Materials Sciences and Engineering, University of Science and Technology Beijing, Beijing 100083, China., Yuan W; Department of Chemistry, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Publikováno v:
ACS omega [ACS Omega] 2024 May 08; Vol. 9 (20), pp. 22352-22359. Date of Electronic Publication: 2024 May 08 (Print Publication: 2024).