An LSTM+ model for managing epidemics : using population mobility and vulnerability for forecasting COVID-19 hospital admissions
Year of publication: |
2023
|
---|---|
Authors: | Ray, Arindam ; Jank, Wolfgang ; Dutta, Kaushik ; Mullarkey, Matthew |
Published in: |
INFORMS journal on computing : JOC ; charting new directions in operations research and computer science ; a journal of the Institute for Operations Research and the Management Sciences. - Linthicum, Md. : INFORMS, ISSN 1526-5528, ZDB-ID 2004082-9. - Vol. 35.2023, 2, p. 440-457
|
Subject: | COVID-19 | epidemic | forecasting | hospital demand management | LSTM | population mobility | social vulnerability | Coronavirus | Krankenhaus | Hospital | Prognoseverfahren | Forecasting model | Epidemie | Epidemic | Binnenwanderung | Internal migration | Sterblichkeit | Mortality | Mobilität | Mobility | Prognose | Forecast |
-
Uneven recovery from the COVID-19 pandemic: post-lockdown human mobility across Chinese cities
Liu, Yanyan, (2021)
-
Forecasting for COVID-19 has failed
Ioannidis, John P. A., (2022)
-
Koenen, M. F., (2020)
- More ...
-
Impact of mobility based network on COVID-19 spread
Ray, Arindam, (2022)
-
Efficient automatic search query formulation using phrase-level analysis
Kajanan, Sangaralingam, (2014)
-
Modeling of financial supply chain
Gupta, Sushil, (2011)
- More ...