首页|基于注意力机制BiLSTM-CRF模型的电网故障处置知识图谱构建技术研究

基于注意力机制BiLSTM-CRF模型的电网故障处置知识图谱构建技术研究

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当前电网运行海量数据未充分挖掘,且调度信息具有多源异构、非结构化的特征,电力调度无法及时得到有效故障信息,致使在抢修工作中调度处置效率降低,故障信息传递不及时、不准确等情况.本文提出基于注意力机制BiLSTM-CRF模型的电网故障处置知识图谱构建技术,依托构建的电网故障处置知识图谱,高效筛选电网故障有效信息,形成智能故障辅助决策应用,切实提高电网故障抢修效率.最后通过实验证明了该文所构建模型的有效性.其中在预案文本分类、命名实体识别和关系抽取方面,该模型与传统模型相比,其精确率、召回率及综合评价指标F1值均有明显提升.
Research on Construction Technology of Knowledge Graph for Power Grid Fault Handling Based on Attention Mechanism Bilstm-CRF Model
In view of the fact that the massive data in the current power grid operation has not fully mined effective information,and the dispatching information is heterogeneous and unstructured from multiple sources,power dispatching cannot obtain effective fault information in a timely manner,resulting in a reduction in the efficiency of dispatching and processing of power dispatching during emergency repair work,and fault information The delivery is not timely or accurate,etc.This paper proposes a power grid fault handling knowledge graph construction technology based on the attention mechanism BiLSTM-CRF model.Relying on the constructed power grid fault handling knowledge graph,it can efficiently screen effective information about power grid faults,form an intelligent fault auxiliary decision-making application,and effectively improve the efficiency of power grid fault repair.Finally,the effectiveness of the model constructed in this paper was demonstrated through experimental design.In terms of text classification for contingency plans,named entity recognition,and relationship extraction,compared with the traditional model,the accuracy rate,recall rate and comprehensive evaluation index F1 value of the proposed model are significantly improved.

knowledge graphpower grid failureattention mechanismmulti-source heterogeneous

杜刃刃、范俊秋、袁龙、谢才科、宋达、罗希、谢威

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贵州电网有限责任公司贵安供电局,贵州贵阳 550025

知识图谱 电网故障 注意力机制 多源异构

中国南方电网有限责任公司科技项目贵州省科技支撑项目

GZKJXM20210413黔科合支撑[2023]一般345

2024

电力大数据
贵州电力试验研究院 贵州省电机工程学会

电力大数据

影响因子:0.047
ISSN:2096-4633
年,卷(期):2024.27(5)