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COVID-19 Sürecinde Turizm Acentelerinin Web Sitelerindeki Ziyaretçi Sayısındaki Değişimin Makine Öğrenmesi Yöntemleriyle Tahmin Edilmesi
2022
Journal:  
Sosyoekonomi
Author:  
Abstract:

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.

Keywords:

Estimating The Changes In The Number Of Visitors On The Websites Of The Tourism Agencies In The Covid-19 Process By Machine Learning Methods
2022
Journal:  
Sosyoekonomi
Author:  
Abstract:

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.

Keywords:

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Sosyoekonomi

Field :   Sosyal, Beşeri ve İdari Bilimler

Journal Type :   Uluslararası

Metrics
Article : 916
Cite : 4.217
2023 Impact : 0.196
Sosyoekonomi