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基于改进DRDPG算法的计算机网络路由优化技术要点研究

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为了提高智能路由的服务稳定性,同时满足用户的各种网络使用需求.研究过程利用改进的深层递归确定性策略梯度算法优化智能路由的控制层,改进点为引入双向长短期记忆网络,替代算法模型的全连接神经网络,从而提高其对周期性流量的记忆能力.优化后的控制层能够根据用户需求规划出更为合理的网络路由.经过仿真检验,改进的深层递归确定性策略梯度算法在平均延时、网络抖动、平均丢包率三个指标上全面优于同类算法.
Research on the optimization technology of computer network routing based on improved DRDPG algorithm
In order to improve the service stability of intelligent routing,and to meet the various network use needs of users.The research process uses the improved deep recursive deterministic strategy gradient algorithm to optimize the control layer of in-telligent routing.The improvement point is to introduce the bidirectional long and short-term memory network,and replace the fully connected neural network of the algorithm model,so as to improve its memory ability for periodic traffic.The optimized control layer can plan a more reasonable network route according to the user needs.After simulation test,the improved deep gradient algo-rithm of recurrent deterministic strategy is better than the similar algorithm in terms of average delay,network jitter and average packet loss rate.

improving DRDPG algorithmintelligent routing model of computer networkrouting optimization

李丹

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哈尔滨职业技术学院电子与信息工程学院,哈尔滨 150081

改进DRDPG算法 计算机网络智能路由模型 路由优化

2024

现代计算机
中大控股

现代计算机

影响因子:0.292
ISSN:1007-1423
年,卷(期):2024.30(22)