About: Curve-fitting approach for COVID-19 data and its physical background

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Curve-fitting approach for COVID-19 data and its physical background Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Curve-fitting approach for COVID-19 data and its physical background
Creator	Inoue, Kenichi Nishimoto, Yoshiro
Source	MedRxiv
abstract	Forecast of the peak-out and settling timing of COVID-19 at an early stage should help the people how to cope with the situation. Curve-fitting method with an asymmetric log-normal function has been applied to daily confirmed cases data in various countries. Most of the curve-fitting could show good forecasts, while the reason has not been clearly shown. The K value has recently been proposed which can provide good reasoning of curve-fitting mechanism by corresponding a long and steep slope on the K curve with fitting stability. Since K can be expressed by a time differential of logarithmic total cases, the physical background of the above correspondence was discussed in terms of the growth rate in epidemic entropy.
has issue date	2020-07-04(xsd:dateTime)
bibo:doi	10.1101/2020.07.02.20144899
has license	medrxiv
sha1sum (hex)	b466cf0b8f59dea9f9316e40156ca8b373daa527
schema:url	https://doi.org/10.1101/2020.07.02.20144899
resource representing a document's title	Curve-fitting approach for COVID-19 data and its physical background
resource representing a document's body	covid:b466cf0b8f59dea9f9316e40156ca8b373daa527#body_text
is schema:about of	named entity 'stage' named entity 'Since' named entity 'CORRESPONDENCE' named entity 'CURVE' named entity 'PROVIDE' named entity 'PEOPLE' covid:arg/b466cf0b8f59dea9f9316e40156ca8b373daa527 named entity 'confirmed' named entity 'stability' named entity 'curve' named entity 'good' named entity 'good' named entity 'COVID-19' named entity 'log-normal' named entity 'Curve-fitting' named entity 'entropy' named entity 'entropy' named entity 'entropy' named entity 'spread sheet' named entity 'Japan' named entity 'curve-fitting' named entity 'macroscopic' named entity 'Germany' named entity 'Fermi-Dirac statistics' named entity 'epidemic' named entity 'Japan' named entity 'Japan' named entity 'Japan' named entity 'logarithm' named entity 'entropy' named entity 'logarithm' named entity 'time-variant' named entity 'Log-normal' named entity 'gradient' named entity 'curve-fitting' named entity 'Taiwan' named entity 'curve-fitting' named entity 'epidemic' named entity 'Sweden' named entity 'positive number' named entity 'COVID-19' named entity 'COVID-19' named entity 'Japan' named entity 'Tokyo' named entity 'macroscopic' named entity 'logistic function' named entity 'entropy' named entity 'quantum statistics' named entity 'Japan' named entity 'cumulative distribution' named entity 'total chemical potential' named entity 'ad hoc' named entity 'thermal equilibrium' named entity 'Japan' named entity 'Johns Hopkins University' named entity 'curve-fitting' named entity 'curve-fitting' named entity 'Fermi-Dirac distribution' named entity 'medRxiv' named entity 'downward slope' named entity 'COVID-19' named entity 'entropy' named entity 'Taiwan' named entity 'epidemic' named entity 'logistic function' named entity 'peer review' named entity 'Pauli exclusion principle' named entity 'horizontal axis' named entity 'New York' named entity 'Excel' named entity 'Japan' named entity 'population densities' named entity 'Japan' named entity 'state of emergency' named entity 'entropy' named entity 'functional form' named entity 'lognormal' named entity 'log-normal' named entity 'Wuhan' named entity 'June 1' named entity 'entropy' named entity 'peer review' named entity 'Italy' named entity 'curve-fitting'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software