Zoo Seasonal Visitors Prediction Using Machine Learning Algorithm

Abstract—The purpose of this research study is to investigate the application of linear regression to forecast, based on the date entered, the number of visits to a zoo during a specific season. The study's main objective is to discover the important variables that affect seasonal attendance, such as weather, the day of the week, and zoo events. By applying linear regression, this research provides a method for forecasting attendance with greater accuracy and efficiency. The findings of this study can help zoo management make data-driven staffing, pricing, and marketing decisions that will improve visitor experiences and generate more income. The results of this study demonstrate the potential advantages of employing data-driven approaches to enhance decision-making and contribute to the expanding field of machine learning in the tourism business.