应用知识图谱的电力设备产品质量预测研究

Research on product quality prediction of power equipment by using knowledge graph

常规电力设备产品质量预测效果不佳,为此提出基于知识图谱的电力设备产品质量预测方法。根据当前测定需求及标准的变化,先进行基础预测指标的设定,采用多阶的方式打破预测覆盖范围受到的限制,构建多阶交叉预测结构,后设计知识图谱电力设备产品质量预测模型,采用图谱回归测定的方式来实现质量预测处理。实验结果表明:在该文提出的方法应用后,质量预测的最终F1值可以达到0.8以上,具有更好的预测效果和实际应用价值。

The quality prediction effect of conventional power cquipment is not good,so the quality prediction method of power equipment based on knowledge graph is proposed.According to the current change of demand and standards,the basic prediction index set,using the way of multiple order to break the prediction coverage limit,build multi-order cross prediction structure,after the design knowledge map power equipment product quality prediction model,using the way of atlas regression determination to achieve quality prediction processing.The cxperimental results show that after the application of the proposed mcthod,the final F1 value of quality prediction can reach more than o.8,which has better prediction effect and practical application value.