This study presents a state-of-the-art approach to optimize fuzzy inference systems (FIS) using genetic algorithms (GA), a powerful evolutionary method inspired by natural selection. Traditional FIS development relies on heuristic tuning of the rule base and relevance functions, which can be inefficient. This study systematically optimizes the FIS rule base, which improves the accuracy, flexibility, and robustness of decision systems. Experimental results show that the complexity of the rule base is significantly reduced while maintaining the system performance. The study also highlights the importance of GA operators such as selection, crossover, and mutation to achieve global optimality. Such integration helps develop intelligent systems that can adapt to real-world situations, yielding promising results for expert systems, automation, and control applications.

This work is dedicated to exploring the application of machine learning (ML) in transforming business processes within the digital economy. The study examines the potential of ML algorithms for automating management, forecasting key performance indicators (KPIs), and optimizing resource allocation. The article provides a detailed overview of theoretical foundations, the methodology for developing software solutions, and the results of experiments conducted on real-world data from logistics and e-commerce. Examples of using linear regression, random forest, gradient boosting, and neural networks are presented, demonstrating their effectiveness in enhancing productivity and reducing costs. The work emphasizes the strategic role of ML as a tool for achieving competitive advantages and suggests directions for further research in adapting these technologies to various industries.

This article examines the impact of digital technologies and artificial intelligence on logistics between Russia, China and Uzbekistan. The theoretical and practical aspects of Al application in logistics systems are described, as well as the possibilities of optimizing processes, increasing efficiency and reducing costs are analyzed. The strategic importance of logistics for the development of the economics of these countries in the context of globalization is emphasized.

This article examines the role of algorithms in solving artificial intelligence (Al) problems and ways to increase their effectiveness. The main algorithmic approaches used in systems (Al) will be analyzed, as well as their advantages and limitations will be highlighted. The article uses advanced literature that will help to study the theoretical and practical aspects of artificial intelligence algorithms.

This article covers the process of improving the quality of videos, optimizing and analyzing images. The article reviews modem technologies, in particular, methods based on artificial intelligence and machine learning, as well as approaches such as reducing noise in videos, image restoration, color correction and improving video compression.