Application of Artificial Intelligence Algorithms in Traffic Prediction and Resource Scheduling in 5G Networks
5G networks face many new challenges,such as the sharp increase in data traffic,the strict requirements of network latency,etc.By introducing artificial intelligence algorithms,these problems can be dealt with more effectively.Ai can help predict traffic patterns,thus allo-cating network resources more efficiently and improving the overall efficiency of the network.Considering the shortcomings of previous network traffic prediction models in accuracy and generalization ability,this paper introduced 5G network slicing technology,combined with K-means clustering algorithm and support vector machine SVM regression prediction model KM-SVM for traffic prediction.First,the K-means algorithm was used to cluster the data,and then SVM was used to train the regression model to achieve the prediction of the traffic data.Then,according to the prediction results,the slicing resource strategy is synthesized based on the re-source scheduling method of user priority.Through accurate traffic prediction and resource scheduling,users can ensure that they get more stable and faster services when using 5G net-works,and optimize user experience.
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