Entropy of Shannon from Geometrical Modeling of Covid-19 Infections Data: The Cases of USA and India

被引:0
|
作者
Nieto-Chaupis, Huber [1 ]
机构
[1] Univ Autonoma Peru, Panamer Km 16-3 Villa El Salvador Lima, Lima, Peru
关键词
Covid-19; Shanon's entropy; Geometry modeling;
D O I
10.1007/978-3-031-16072-1_37
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Between the end of second semester of 2020 and along the first semester of 2021, Covid-19 has had a strong impact on United States and India as seen at the official statistics exhibiting a big number of new infections as well as fatalities, particularly India that have had sharp peaks at March 2021. The present paper addresses the question if there is a entropic nature in these cases from an intuitive model based at simple geometries that adjust well the histograms of new infections versus time. Although the geometry-based models might not be satisfactory in all, it provides a view that would lead to answer intrinsic questions related to the highest peaks of pandemic if these have a nature cause or are strongly related to disorder as dictated by Shannon's entropy for instance.
引用
收藏
页码:505 / 513
页数:9
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