The use of a recurrent neural network model with separated time-series and lagged daily inputs for waste disposal rates modeling during COVID-19

A new modeling framework is proposed to estimate mixed waste disposal rates in a Canadian capital city during the pandemic. Different Recurrent Neural Network models were developed using climatic, socioeconomic, and COVID-19 related daily variables with different input lag times and study periods. I...

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Detalles Bibliográficos
Autores principales: Vu, Hoang Lan, Ng, Kelvin Tsun Wai, Richter, Amy, Kabir, Golam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423673/
https://www.ncbi.nlm.nih.gov/pubmed/34513573
http://dx.doi.org/10.1016/j.scs.2021.103339

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423673/
https://www.ncbi.nlm.nih.gov/pubmed/34513573
http://dx.doi.org/10.1016/j.scs.2021.103339

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