电力需求侧管理2025，Vol.27Issue(1)：94-100,7.DOI:10.3969/j.issn.1009-1831.2025.01.015
基于并行混合神经网络的95598工单情感分析
Sentiment analysis of 95598 work orders based on parallel hybrid neural networks
摘要
Abstract
In order to solve the problem of serious consequences caused by untimely processing of 95598 emergency work orders,a paral-lel hybrid neural network sentiment analysis model for power work order texts based on attention mechanism is proposed to meet the re-quirements of automatic intelligent reminders for emergency work orders.Firstly,a sentiment analysis dataset for electric power work order texts is generated by manually annotating the emotional urgency of work order texts through sentiment dictionaries and rule sets;Using text pre trained BERT model for text vectorization;Then,use text convolutional neural network(TextCNN)and bidirectional long short term memory(BiLSTM)to extract local and contextual features of the text,respectively,and perform feature fusion;Using attention mechanism to enhance the ability of the model to recognize key information in the fused text features.The calculation results show that the neural net-work model that integrates attention mechanism has better performance in sentiment classification of power work order texts compared to other deep learning models.关键词
95598工单/情感分析/文本卷积神经网络/长短期记忆网络/注意力机制Key words
95598 work order/emotional analysis/text convolutional neural network/long short-term memory network/attention mechanism分类
信息技术与安全科学引用本文复制引用
张霞,刘宝龙,何湘英,王恭玥,刘晓捷..基于并行混合神经网络的95598工单情感分析[J].电力需求侧管理,2025,27(1):94-100,7.基金项目
国网常州供电公司科技项目(CZ2024017) （CZ2024017）
