The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach
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.contributor.authorID | 17411 | tr_TR |
dc.date.accessioned | 2024-04-29T12:24:20Z | |
dc.date.available | 2024-04-29T12:24:20Z | |
dc.date.issued | 2022 | |
dc.department | Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
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. | en_US |
dc.description.publishedMonth | 3 | |
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. | en_US |
dc.identifier.doi | 10.1002/cpe.6774 | |
dc.identifier.issn | 15320626 | |
dc.identifier.issue | 6 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12416/8074 | |
dc.identifier.volume | 34 | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Concurrency and Computation: Practice and Experience | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Coronavirus | en_US |
dc.subject | Covid-19 | en_US |
dc.subject | Forecasting Method | en_US |
dc.subject | Visual Data Analysis | en_US |
dc.title | The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach | tr_TR |
dc.title | The Effect of Population and Tourism Factors on Covid-19 Cases in Italy: Visual Data Analysis and Forecasting Approach | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication |
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