| Abstract [eng] |
The article intends to identify the problems associated with the detection of human traffic in public transport and provide ideas on how to automate the forecasting of human traffic using statistical-mathematical and artificial intelligence neural network models. The aim is for the application of these models to create more optimal public transport routes that are more convenient for passengers. The paper examines the most advanced artificial intelligence technologies for object recognition, location, and prediction. Models of artificial neural networks for calculating the maximum number of people in public transport have been developed, which are trained with real data. The best working model is presented. |
