Nonlinear Prediction for the COVID-19 Data Based on Quadratic Kalman Filtering
Considering the application of prediction techniques to support the decision-making process during a dynamic environment such as the one faced during the COVID-19 pandemic, demands the evaluation of several different strategies to compare and define the m
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Joao Alexandre Lobo Marques Francisco Nauber Bernardo Gois José Xavier-Neto Simon James Fong
Predictive Models for Decision Support in the COVID-19 Crisis
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Joao Alexandre Lobo Marques Francisco Nauber Bernardo Gois José Xavier-Neto Simon James Fong •
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Predictive Models for Decision Support in the COVID-19 Crisis
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Joao Alexandre Lobo Marques Laboratory of Neuroapplications University of Saint Joseph Macau, Macao José Xavier-Neto Government Intelligence Cell Secretary of Health of the Government of the State of Ceara Fortaleza, Brazil
Francisco Nauber Bernardo Gois Machine Learning Department Secretary of Health of the Government of the State of Ceara Fortaleza, Brazil Simon James Fong Department of Computer and Information Science University of Macau Macau, Macao
ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISBN 978-3-030-61912-1 ISBN 978-3-030-61913-8 (eBook) https://doi.org/10.1007/978-3-030-61913-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodolog
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