Design of Intelligent Data Transmission System in Information Communication Network Engineering Based on Deep Learning
Aiming at the increasing data traffic and network complexity in modern communication networks,this paper proposes a design scheme of intelligent data transmission system based on deep learning.The system uses deep neural network to model and analyze the network environment and data flow characteristics,and realizes adaptive transmission optimization,intelligent routing,active security protection and rapid fault recovery.By constructing a traffic prediction model based on Long Short-Term Memory(LSTM),a routing algorithm based on deep reinforcement learning,an intrusion detection model based on self-encoder,etc.,the system can optimize transmission paths,adjust transmission parameters,and take security protection measures.Experimental results show that,compared with traditional methods,the intelligent system improves throughput,reduces delay,reduces packet loss rate and speeds up fault recovery.
deep learningintelligent data transmissionnetwork optimization
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