BUILDING A SELF-LEARNING AND SELF-ADJUSTING GENERAL MANAGEMENT SYSTEM FOR DIGITAL ENTERPRISE

The article presents an intelligent quality management system based on self-learning neural networks for the design of oil product pipelines. The system combines deep learning methods with physics- informed neural network models, which makes it possible to optimize pipeline parameters in real time, predict emergency situations and adapt to changing operating conditions. The proposed approach demonstrates a 30-40% increase in the accuracy of calculations compared to traditional methods while reducing the time spent on design.