The Prediction Analysis of COVID-19 Cases Using ARIMA and KALMAN Filter Models: A Case of Comparative Study
The time series technique in machine learning is one of the important spaces for analysis and prediction. It includes many approaches to predict that involves time component. In the chapter, two approaches, i.e., autoregressive integrated moving average (
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Chinmay Chakraborty Amit Banerjee Lalit Garg Joel J. P. C. Rodrigues Editors
Internet of Medical Things for Smart Healthcare Covid-19 Pandemic
Studies in Big Data Volume 80
Series Editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
The series “Studies in Big Data” (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence including neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. ** Indexing: The books of this series are submitted to ISI Web of Science, DBLP, Ulrichs, MathSciNet, Current Mathematical Publications, Mathematical Reviews, Zentralblatt Math: MetaPress and Springerlink.
More information about this series at http://www.springer.com/series/11970
Chinmay Chakraborty Amit Banerjee Lalit Garg Joel J. P. C. Rodrigues •
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Editors
Internet of Medical Things for Smart Healthcare Covid-19 Pandemic
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Editors Chinmay Chakraborty Department of Electronics and Communication Engineering Birla Institute of Technology Ranchi, Jharkhand, India Lalit Garg Department of Information and Communication Technology University of Malta Msida, Malta
Amit Banerjee Department of Physics Bidhan Chandra College (Kazi Nazrul University) Asansol, West Bengal, India Joel J. P. C. Rodrigues Federal University of Piauí Teresina, PI, Brazil Instituto de Telecomunicações Covilhã, Portugal
ISSN 2197-6503 ISSN 2197-6511 (electronic) Studies in Big Data ISBN 978-981-15-8096-3 ISBN 978-981-15-8097-0 (eBook) https://doi.org/10.1007/978-981-15-8097-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 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
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