I. Introduction
Network traffic prediction refers to the utilization of histori-cal network traffic data and other relevant information to fore-cast future network traffic data or trends. This practice holds significant importance for network resource management and optimization, anomaly detection, fault detection, load balancing, and other aspects of network planning and management. For instance, accurately predicting metrics such as bandwidth utilization in a network can aid service providers in antici-pating imminent network congestion. This proactive insight enables them to undertake network expansion, adjustments, and optimization, thereby enhancing overall communication network efficiency. With the emergence of edge computing, the Internet of Things (loT), and 5G technology, network operations have become increasingly complex and diversified. Network traffic now exhibits characteristics such as bursts, nonlinearity, and autocorrelation, presenting new challenges for network traffic prediction.