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pro vyhledávání: '"Shen, Zuojun Max"'
In time series forecasting, decomposition-based algorithms break aggregate data into meaningful components and are therefore appreciated for their particular advantages in interpretability. Recent algorithms often combine machine learning (hereafter
Externí odkaz:
http://arxiv.org/abs/2212.06620
Autor:
Huang, Yiduo, Shen, Zuojun Max
The recovery of the public transportation system is critical for both social re-engagement and economic rebooting after the shutdown during pandemic like COVID-19. In this study, we focus on the integrated optimization of service line reopening plan
Externí odkaz:
http://arxiv.org/abs/2109.03940
Autor:
Shen, Zuojun Max1,2 (AUTHOR) maxshen@berkeley.edu, Sun, Yiqi3 (AUTHOR)
Publikováno v:
Journal of Operations Management. Apr2023, Vol. 69 Issue 3, p359-383. 25p.
During the COVID-19 pandemic, public transportation systems worldwide faced many challenges, including significant loss of ridership. Public agencies implemented various COVID-19-related policies to reduce transmission, such as reducing service frequ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::67c2dc5d112df80d98c2a8f5fc579f2e
https://escholarship.org/uc/item/9350c32g
https://escholarship.org/uc/item/9350c32g
Autor:
Shen, Zuojun Max, Sun, Yiqi
Publikováno v:
Journal of Operations Management
The coronavirus/SARS-CoV-2 (COVID-19) outbreak has caused severe supply chain disruptions in practically all industries worldwide. Online e-commerce platforms, which interact directly with various industries and service numerous consumers, have becom