Integration and Analysis of Network Information System Operation and Maintenance Data Based on Artificial Intelligence Technology

Nowadays, the operation and management of network information systems face numerous challenges, especially in data management and analysis. This study aims to improve the data integration and analysis process of network information system operation and maintenance through artificial intelligence(AI) technology. First, the study intelligently classifies and preprocesses operation and maintenance data by applying machine learning(ML) algorithms, extracts key information using natural language processing techniques, and subsequently conducts in-depth data correlation analysis using a deep learning(DL) model, so as to effectively identify potential bottlenecks in the system and early warning failure signals. The aspect of improving the learning rate when parameter tuning increases the accuracy from 88% to 90%, indicating that the faster learning rate helps the model to better adapt to the data, although there may be a risk of overfitting. The findings of this paper will provide new ideas for the operation and maintenance of networked information systems and will be useful for the improvement of the operation quality of other information systems.