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The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach

dc.contributor.authorUğuz, Sezer
dc.contributor.authorYağanoğlu, Mete
dc.contributor.authorÖzyer, Barış
dc.contributor.authorÖzyer, Gülşah Tümüklü
dc.contributor.authorTokdemir, Gül
dc.contributor.authorID17411tr_TR
dc.date.accessioned2024-04-29T12:24:20Z
dc.date.available2024-04-29T12:24:20Z
dc.date.issued2022
dc.departmentÇankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractAt 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.en_US
dc.description.publishedMonth3
dc.identifier.citationUğuz, 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.en_US
dc.identifier.doi10.1002/cpe.6774
dc.identifier.issn15320626
dc.identifier.issue6en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12416/8074
dc.identifier.volume34en_US
dc.language.isoenen_US
dc.relation.ispartofConcurrency and Computation: Practice and Experienceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCoronavirusen_US
dc.subjectCovid-19en_US
dc.subjectForecasting Methoden_US
dc.subjectVisual Data Analysisen_US
dc.titleThe effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approachtr_TR
dc.titleThe Effect of Population and Tourism Factors on Covid-19 Cases in Italy: Visual Data Analysis and Forecasting Approachen_US
dc.typeArticleen_US
dspace.entity.typePublication

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