软件导刊2024，Vol.23Issue(6)：18-24,7.DOI:10.11907/rjdk.231451
风电业务流程剩余时间预测与系统应用
Wind Power Business Process Remaining Time Prediction and System Application
摘要
Abstract
Aiming at the complexity of industrial scene event logs and the small amount of data in industrial scenarios,a remaining time pre-diction method based on time convolutional network is proposed.Firstly,causal convolution is used to model process instance data.Then,the model is trained on track prefixes of different lengths to improve the pertinence of the model.Finally,the remaining time prediction model is used in the actual wind power operation and maintenance business scenario to develop the wind power operation and maintenance business sys-tem to realize the visual display of work ticket form data and event log data.Compared with the traditional remaining time prediction method,the prediction effect of the proposed method is significantly improved,and the average absolute error is reduced by an average of 5%.The de-veloped wind power wind power operation and maintenance business system can predict the remaining time in the process of invoicing unfin-ished work tickets,and realize business process overtime alarms.关键词
业务流程分析/剩余时间预测/时间卷积网络/风电业务流程/流程可视化Key words
business process analysis/remaining time prediction/temporal convolution network/wind power business process/process vi-sualization分类
信息技术与安全科学引用本文复制引用
李建元,田玉超,尹昱妍,田甜,刘新锋..风电业务流程剩余时间预测与系统应用[J].软件导刊,2024,23(6):18-24,7.基金项目
国家自然科学基金项目(51975332) （51975332）
山东省重点研发计划(重大科技创新工程)项目(2021CXGC011204) （重大科技创新工程）
