Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
