山东电力技术2026，Vol.53Issue(8)：111-124,14.DOI:10.20097/j.cnki.issn1007-9904.250451
基于改进DeBERTa-DPCNN神经网络的电力工单识别技术研究
Research on Power Grid Work Order Recognition Technique Based on Improved DeBERTa-DPCNN Neural Network
摘要
Abstract
Aiming to address the challenges of inadequate term coverage,insufficient feature extraction from short texts,and low robustness in the current electric power work order recognition technology,we propose an intelligent recognition model for power grid work orders,named DeDPC-P.DeDPC-P integrates an enhanced version of the DeBERTa-Chinese model with a Deep Pyramid Convolutional Neural Network(DPCNN).This method leverages a pre-trained Chinese DeBERTa model,enhanced by expanding its lexicon with domain-specific power terminology and fine-tuning it through adversarial training strategies.This approach strengthens the model's semantic understanding of power-related terms and its robustness against noise interference.Furthermore,the DPCNN employs multi-layer convolutional structures and residual connections to comprehensively extract local key features and long-distance dependencies from work order texts,thereby constructing an end-to-end classification framework.Experimental results demonstrate that,on a real-world dataset of 27 680 power work orders,DeDPC-P achieves a macro-F1 score of 0.941 0,improving by 3.14%and 6.09%compared to standalone DeBERTa and DPCNN models,respectively.DeDPC-P achieves a macro precision of 0.941 5 and exhibits strong robustness in noisy work order scenarios.关键词
工单识别/DeBERTa-Chinese模型/深度金字塔卷积神经网络模型/电力系统Key words
power grid work order/DeBERTa-Chinese/DPCNN/power system分类
信息技术与安全科学引用本文复制引用
刘嘉熹,高丽媛,付昀夕,郭光来,张沛尧..基于改进DeBERTa-DPCNN神经网络的电力工单识别技术研究[J].山东电力技术,2026,53(8):111-124,14.基金项目
国网信息通信产业集团有限公司科技创新项目"面向新型电力系统的数字化配电网精准规划平台、协同作业枢纽与能源绿证交易研究专项"(SGIT0000KJJS2400504). Science and Technology Project of State Grid Information&Telecommunication Group Company"Research Project of Digitalized Distribution Grid Precision Planning Platform,Cooperative Operation Hub and Energy Green Certificate Transaction for New Electricity Systems"(SGIT0000KJJS2400504). （SGIT0000KJJS2400504）
