Prototype of an Expert System for Analyzing Small and Medium Enterprises Using Associative Rules and GIS Technologies

This study presents a prototype of an expert system for analyzing small and medium enterprises (SMEs), combining data mining methods and geographic information systems (GIS). The solution, developed in Python, includes the Apriori algorithm for identifying associative rules among types of economic activities (OKVED) and tools for geospatial visualization. The key contribution of this research is the integration of associative rule analysis methods with GIS technologies, allowing the identification of stable relationships between the sectoral specialization of enterprises and their territorial distribution. A software module has been implemented for data processing, interacting with the DaData service API, ensuring the relevance and reliability of the source data. The results can be applied by government agencies to optimize support measures for SMEs, as well as by entrepreneurs for analyzing market niches and competitive environments. The developed hybrid artificial intelligence systems for the digital transformation of the economy, combining interpretability, accuracy, and expert assessments, play a crucial role in ensuring sustainable industrial development.