深度自编码下电力通信网络风险态势评估方法

Evaluation Method of Power Communication Network Risk Situation Based on Deep Auto-Encoding

为了提高深度自编码下电力通信网络风险感知和预测能力,提出基于线性随机编码控制的电力通信网络风险态势评估方法。构建电力通信网络风险态势感知的随机编码模型,结合加权随机编码控制方法实现电力通信网络风险态势数据挖掘,通过冗余代码混淆的方法进行电力通信网络风险特征的深度自编码设计,提高电力通信网络风险评估和稳态控制能力。仿真结果表明,采用该方法进行电力通信网络风险态势评估的稳定性较好,通信网络的信道均衡控制能力较强。

In order to improve the risk perception and prediction ability of electric power communication network under deep auto-encoding,a method of power communication network risk situation assessment based on linear random coding control is proposed.Construct a random coding model for power communication network risk situation awareness,combine with weighted random coding control method to realize power communication network risk situation data mining,and use redundant code obfuscation method to carry out in-depth self-encoding design of power communication network risk characteristics to improve power communication network Risk assessment and steady�state control capabilities.The simulation results show that the stability of the risk situation assessment of the power communication network by this method is better,and the communication network has a stronger ability to control the channel balance.