Analysis on the Application of Artificial Intelligence Network Algorithm in Network Information Processing

With the explosive growth of network information, traditional information processing methods such as rule-based filtering systems face challenges like low efficiency and insufficient accuracy, making them inadequate for handling high-speed, heterogeneous real-time data. This paper focuses on core technologies in artificial intelligence network algorithms, including deep learning, convolutional neural networks (CNN), and recurrent neural networks (RNN) applications in network information processing. By examining algorithmic principles and their operational mechanisms across scenarios like data processing and real-time analysis, this study demonstrates the critical advantages of AI algorithms in enhancing network processing efficiency, improving intelligence, and ensuring security. The research provides theoretical support and practical guidance for intelligent upgrades of network information processing systems, contributing to the development of more efficient and reliable information ecosystems.