Estimating the Changes in the Number of Visitors on the Websites of the Tourism Agencies in the COVID-19 Process by Machine Learning Methods

Yıl 2022, , 11 - 26, 29.07.2022

Mehmet Kayakuş

https://doi.org/10.17233/sosyoekonomi.2022.03.01

Cited By: 2

Öz

In this study, the number of visitors of five different tourism agencies was tried to be estimated by machine learning method using the number of cases and deaths in Europe during COVID-19. Artificial neural network (ANN), support vector regression (SVR), and multiple linear regression (MLR) were used as machine learning models. A model consisting of two independent variables and one dependent variable was created. According to the analysis made according to three different techniques, the most successful results; According to R2, it was seen that ANN, DVR, and MDR, and according to other statistical methods, ANN, MDR, and DVR, respectively.

Anahtar Kelimeler

COVID-19 Pandemic, Tourism Agency, Website, Number of Visitors, Machine Learning

COVID-19 Sürecinde Turizm Acentelerinin Web Sitelerindeki Ziyaretçi Sayısındaki Değişimin Makine Öğrenmesi Yöntemleriyle Tahmin Edilmesi

Öz

Bu çalışmada COVID-19 süresince Avrupa’daki vaka ve ölüm sayıları bilgileri kullanılarak beş farklı turizm acentesinin ziyaretçi sayısı makine öğrenmesi yöntemiyle tahmin edilmeye çalışılmıştır. Yöntem olarak makine öğrenmesi modellerinden yapay sinir ağları (YSA), destek vektör regresyonu (DVR) ve çoklu doğrusal regresyon (ÇDR) kullanılmıştır. İki bağımsız değişken ve bir bağımlı değişkenden oluşan model oluşturulmuştur. Üç farklı tekniğine göre yapılan analize göre en başarılı sonuçların; R2’ye göre YSA, DVR ve ÇDR, diğer istatiksel yöntemlere göre de sırasıyla YSA, ÇDR ve DVR olduğu görülmüştür.

Anahtar Kelimeler

COVID-19 Salgını, Turizm Acentesi, Web Sitesi, Ziyaretçi Sayısı, Makine Öğrenmesi

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