Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bora Oztekin"'
Autor:
Qingchun Li, Yang Yang, Wanqiu Wang, Sanghyeon Lee, Xin Xiao, Xinyu Gao, Bora Oztekin, Chao Fan, Ali Mostafavi
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract The objective of this study was to investigate the importance of multiple county-level features in the trajectory of COVID-19. We examined feature importance across 2787 counties in the United States using data-driven machine learning models
Externí odkaz:
https://doaj.org/article/ef266603da604585805112e255324a7e
Publikováno v:
Applied Network Science, Vol 6, Iss 1, Pp 1-18 (2021)
Abstract The objective of this study is to examine the transmission risk of COVID-19 based on cross-county population co-location data from Facebook. The rapid spread of COVID-19 in the United States has imposed a major threat to public health, the r
Externí odkaz:
https://doaj.org/article/56c475742649493aa10d3c34e1bf4e5c
Publikováno v:
Environment and Planning B: Urban Analytics and City Science. 49:2378-2391
The objective of this study is to examine spatial patterns of disaster impacts and recovery of communities based on fluctuations in credit card transactions (CCTs). Such fluctuations could capture the collective effects of household impacts, disrupte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::026447d8ebc4a522c71884c0722fd668
https://doi.org/10.1177/23998083221090246
https://doi.org/10.1177/23998083221090246
Autor:
Xinyu Gao, Qingchun Li, Bora Oztekin, Xin Xiao, Sanghyeon Lee, Ali Mostafavi, Wanqiu Wang, Chao Fan, Yang Yang
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports
Scientific Reports
The objective of this study was to investigate the importance of multiple county-level features in the trajectory of COVID-19. We examined feature importance across 2787 counties in the United States using data-driven machine learning models. Existin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc759fd9f01e2718247e07a8580378ef
http://arxiv.org/abs/2101.03458
http://arxiv.org/abs/2101.03458
Publikováno v:
Computers, Environment and Urban Systems. 83:101514
The objective of this study is to examine and quantify the relationships among sociodemographic factors, damage claims, and social media attention on areas during natural disasters. Social media has become an important communication channel for peopl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ed69d7017e1cae38c50ca04ff5490bf
https://doi.org/10.1016/j.compenvurbsys.2020.101514
https://doi.org/10.1016/j.compenvurbsys.2020.101514
Autor:
Meng Liu1 MENGLIU@TAMU.EDU, Youzhi Luo1 YZLUO@TAMU.EDU, Limei Wang1 LIMEI@TAMU.EDU, Yaochen Xie1 ETHANYCX@TAMU.EDU, Hao Yuan1 HAO.YUAN@TAMU.EDU, Shurui Gui1 SHURUI.GUI@TAMU.EDU, Haiyang Yu1 HAIYANG@TAMU.EDU, Zhao Xu1 ZHAOXU@TAMU.EDU, Jingtun Zhang1 ZJT6791@TAMU.EDU, Yi Liu1 YILIU@TAMU.EDU, Keqiang Yan1 KEQIANGYAN@TAMU.EDU, Haoran Liu1 LIUHR99@TAMU.EDU, Cong Fu1 CONGFU@TAMU.EDU, Bora Oztekin1 BORA@TAMU.EDU, Xuan Zhang1 XUAN.ZHANG@TAMU.EDU, Shuiwang Ji1 SJI@TAMU.EDU
Publikováno v:
Journal of Machine Learning Research. 2021, Vol. 22, p1-9. 9p.