Forecasting COVID-19 pandemic using an echo state neural network-based framework

被引：0
|
作者：
Larcher, José Henrique Kleinübing [1 ]
Da Silva, Ramon Gomes [2 ]
Ribeiro, Matheus Henrique Dal Molin [2 ,3 ]
Dos Santos Coclho, Leandro [1 ,4 ]
Mariani, Viviana Cocco [1 ,4 ]
机构：
[1] Pontifical Catholic University of Parana (PUCPR), Mechanical Engineering Graduate Program (PPGEM), Curitiba, Brazil
[2] Pontifical Catholic University of Parana (PUCPR), Industrial Systems Engineering Graduate Program (PPGEPS), Curitiba, Brazil
[3] Department of Mathematics, Federal University of Technology - Parana (UTFPR), Pato Branco, Parana, Brazil
[4] Department of Electrical Engineering, Federal University of Parana (UFPR), Curitiba, Parana, Brazil
来源：
Proceedings of the International Joint Conference on Neural Networks | 2021年 / 2021-July卷
关键词：
Auto-regressive - Autoregressive integrated moving average - Coronavirus disease 2019 - Coronaviruses - Echo state networks - Mean absolute error - Moving averages - Percentage error - Root mean square errors - Times series;
D O I：
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学科分类号：
摘要：
38
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