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

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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


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