dc.contributor.author |
Uğuz, Sezer
|
|
dc.contributor.author |
Yağanoğlu, Mete
|
|
dc.contributor.author |
Özyer, Barış
|
|
dc.contributor.author |
Özyer, Gülşah Tümüklü
|
|
dc.contributor.author |
Tokdemir, Gül
|
|
dc.date.accessioned |
2024-04-29T12:24:20Z |
|
dc.date.available |
2024-04-29T12:24:20Z |
|
dc.date.issued |
2022-03-10 |
|
dc.identifier.citation |
Uğuz, Sezer...et.al. (2022). "The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach", Concurrency and Computation: Practice and Experience, Vol.34, No.6. |
tr_TR |
dc.identifier.issn |
15320626 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.12416/8074 |
|
dc.description.abstract |
At the beginning of 2020, the new coronavirus disease (Covid-19), a deadly viral illness, is declared as a public health emergency situation by WHO. Consequently, it is accepted as pandemic that affected millions of people worldwide. Italy is one of the most affected countries by Covid-19 disease among the world. In this article, our main goal is to investigate the effect of intensity of Covid-19 cases based on the population size and tourism factors in certain regions of Italy by visual data analysis. The regions of Lombardia, Veneto, Campania, Emilia-Romagna, Piemonte are the top five regions covering 58.50% of the total Covid-19 cases diagnosed in Italy. It has been shown by visual data analysis that population and tourism factors play an important role in the spread of Covid-19 cases in these five regions. In addition, a prediction model was created using Bi-LSTM and ARIMA algorithms to forecast the number of Covid-19 cases occurring in these five regions in order to take early action. We can conclude that these northern regions have been affected mostly by Covid-19 and the distribution of the resident population and tourist flow factors affected the number of Covid-19 cases in Italy. |
tr_TR |
dc.language.iso |
eng |
tr_TR |
dc.relation.isversionof |
10.1002/cpe.6774 |
tr_TR |
dc.rights |
info:eu-repo/semantics/closedAccess |
tr_TR |
dc.subject |
Coronavirus |
tr_TR |
dc.subject |
Covid-19 |
tr_TR |
dc.subject |
Forecasting Method |
tr_TR |
dc.subject |
Visual Data Analysis |
tr_TR |
dc.title |
The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach |
tr_TR |
dc.type |
article |
tr_TR |
dc.relation.journal |
Concurrency and Computation: Practice and Experience |
tr_TR |
dc.contributor.authorID |
17411 |
tr_TR |
dc.identifier.volume |
34 |
tr_TR |
dc.identifier.issue |
6 |
tr_TR |
dc.contributor.department |
Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü |
tr_TR |