Agile technology for developing an intelligent population development forecasting system

The article is devoted to the development of an intelligent population forecasting system that uses machine learning methods to analyze historical demographic data. The paper considers modern challenges of demographic development that require accurate population forecasting for effective strategic planning. The article presents a description of demographic forecasting methods, formalization and mathematical models, such as linear and polynomial regression, as well as other models that can be used for forecasting. A machine learning model generation module has been developed that automates the process of building forecasting models based on historical demographic data. Data preprocessing functionality has been implemented, including automatic filling of missing values, data normalization and anomaly detection. Machine learning algorithms have been selected and integrated, quality assessment and model optimization have been carried out, and the possibility of retraining models has been provided. An interface for integration with other information systems has been developed. The results obtained demonstrate the flexibility and effectiveness of the proposed approach and the possibility of its use in the field of strategic planning of socio-economic development.