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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier Ltd.
2021
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| Materias: | |
| 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 |