基于深度学习的电力服务调度工单智能处理的研究

为打造以客户为中心的现代供电服务体系,进一步提升为民服务的质量和水平,强化电力保障和优质服务,贵安供电局开展海量工单分析,从而实现服务调度业务薄弱点的发现和改进。因此,提出基于深度学习的工单识别分类技术应用,通过深度学习进行建模、工单的标签特征进行提炼、并建立训练模型进行学习、对故障单和意见单进行识别,优化投诉风险预警与管理工作,缓解服务调度工作人员服务压力。

Research on intelligent processing of power service dispatching order based on deep learning

In order to build a customer-centered modern power supply service system,further improve the quality and level of service for the people,and strengthen power guarantee and quality service,gui’an power supply bureau carries out massive customer demand analysis,so as to realize the discovery and improvement of weak points of service scheduling business.Therefore,the application of classification technology based on deep learning was proposed to optimize the early warning and management of complaint risk and relieve the service pressure of service scheduling staff through deep learning modeling,WLR feature label extraction,model learning training and suspected complaint identification.