COVID-19: Metaheuristic Optimization-Based Forecast Method on Time-Dependent Bootstrapped Data

Fenga, L; Del Castello, C
Date: 11 February 2021
Journal
Journal of Probability and Statistics
Publisher
Hindawi
Publisher DOI
https://doi.org/10.1155/2021/1235973
Related links
https://github.com/pcm-dpc/COVID-19/tree/master/dati-regioni
Abstract
A compounded method—exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques—is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the COVID-19 virus in Italy. Future lines of research, which include ...
A compounded method—exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques—is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the COVID-19 virus in Italy. Future lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.
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Faculty of Environment, Science and Economy

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© 2021 Livio Fenga and Carlo Del Castello. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2021 Livio Fenga and Carlo Del Castello. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.