Comparative analysis of methods for demand forecasting in food courts

The article provides a comparative analysis of modern machine learning methods used for demand forecasting in food courts. Traditional and intelligent approaches are considered, key problems and limitations are highlighted, and the efficiency of different algorithms is evaluated. Particular attention is paid to the effectiveness of machine learning algorithms and their applicability to the food service industry. The analysis is based on the data of domestic and foreign studies.