POSSIBILITIES OF MACHINE LEARNING METHODS FOR FORECASTING THE DEVELOPMENT OF URBAN TERRITORIES
Urban design has always been a spatial process. Since the city is a combination of spaces and connections, both above and under ground, it is especially important to bring territorial planning to the level of spatial modeling. In the paper, the possibilities of machine learning methods for predicting the development of urban areas were investigated, a forecasting model was compiled, and its accuracy was evaluated.