基于机器学习的电力系统通信网数据治理模型

Data governance model of power system communication network based on machine learning

为加强电力系统通信网数据安全管理,提出了一种基于机器学习的电力系统通信网数据治理模型。使用传感器群获取通信网数据安全态势经验池;利用深度长短期神经网络对经验池进行特征提取,建立通信网数据安全态势精准预测机制;利用深度确定性策略构建通信网数据安全态势在线学习与治理策略自主生成之间的多级耦合模型。选取国家电网某电力公司数据进行实验,结果表明,该文所搭建的模型,在数据安全态势预测方面,准确率达到96.28%;在数据安全自主治理策略方面,有效率达到92.81%。该模型可实现通信网数据安全治理策略自主生成。

In order to strengthen the data security management of power system communication network,a data governance model of power system communication network based on machine learning is proposed.Use sensor groups to obtain the experience pool of communication network data security situation;use deep long-term and short-term neural networks to extract features from the experience pool to establish an accurate prediction mechanism for communication network data security situation;use deep deterministic strategies to build communication network data security situation online learning and governance multi-level coupling model between policy autonomous generation.The data of a power company of State Grid is selected for experiments.The results show that the model built in this paper has an accuracy rate of 96.28% in data security situation prediction;and an effective rate of 92.81%in terms of data security autonomous governance strategy.The model communication network data security governance policy is generated autonomously.