The fast development of mobile communication networks has made it harder than ever to make sure that resources are used efficiently, delay is kept low, and service quality is solid. Fifth-generation (5G) and new 6G systems need improved ways to predict traffic, find outliers, and change how resources are used. The goals of this study are to solve these problems by combining optimization theory and machine learning. Optimization uses math to set goals and limits, and machine learning lets computers learn about changing traffic trends in real time.  Together, they increase productivity, cut down on delays, and make the use of energy more efficient.