In this study, a machine learning-based model was built to predict the number of visitors with municipality in Gangwon province using big data with tourist, meteorological observation (air temperature, rainfall, wind speed, wind direction, relative hu...
In this study, a machine learning-based model was built to predict the number of visitors with municipality in Gangwon province using big data with tourist, meteorological observation (air temperature, rainfall, wind speed, wind direction, relative humidity, atmospheric pressure, sunshine duration, solar radiation and cloud fraction) and temporal variables (day, week, and year). The relative influence of meteorological variables was found to be 37.9% on average in Gangwon province through the contribution analysis by input data. As a result of annual predictive analysis, the correlation is 0.81 on average in Gangwon province, with the highest municipality is Inje-gun (0.86) and the lowest municipality is Cheorwon-gun (0.73). And as a result of seasonal analysis, summer (0.93) represents the highest correlation, followed by winter (0.76), spring (0.74), and autumn (0.66). The municipality with the lowest and highest RMSE compared to the average daily number of visitors are Wonju-si (16.6%) and Yeongwol-gun (33.1%), respectively.