Application and Performance Evaluation of Deep Learning Algorithms in Wired Broadband Networks
Deep learning algorithms are mainly introduced to optimize the communication performance in wired broadband networks.Analyzing the adverse effects of bandwidth bottlenecks,signal fading and distortion on communication performance in wired broadband networks,a neural network model is designed based on deep learning and applied to traffic prediction and transmission protocol optimization,aiming to improve the overall efficiency of the network.Through well-designed experiments,the performance of deep learning algorithms for optimizing communication performance in wired broadband networks is evaluated in detail and studied in comparison with traditional methods.The results show that deep learning has significant advantages in enhancing communication performance in wired broadband networks.
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