计算机应用研究2024，Vol.41Issue(7)：2039-2045,7.DOI:10.19734/j.issn.1001-3695.2023.11.0541
基于概念漂移检测的数字孪生流程预测模型
Digital twin process prediction model based on concept drift detection
摘要
Abstract
Predictive process monitoring can provide timely information during the operation of business processes,in order to take measures to address potential risks.How to improve the accuracy of process prediction has always been highly concerned.Most of the existing research methods focus on process prediction in static environments,with few combining digital twin tech-nology for process prediction in dynamic environments.To this end,this paper proposed a method based on concept drift de-tection and constructed a digital twin process prediction model to predict the next activity.Firstly,this method used behavioral relationship between event streams and weight divergence to extract features from activities in the process and obtained the fea-ture sets of data flows.Secondly,this method performed drift detection.It dynamically selected feature sets and input them in-to the artificial intelligence model for training and predicting the next activity.Then,it used advanced technologies such as the Internet of Things and cloud computing to create a digital twin virtual environment.Finally,this paper obtained a digital twin model based on concept drift.It carried out evaluation and analysis on publicly available datasets,and the experimental results show that the proposed method can improve the effectiveness of prediction.关键词
预测性流程监控/活动预测/漂移检测/数字孪生Key words
predictive process monitoring/activity prediction/drift detection/digital twin分类
信息技术与安全科学引用本文复制引用
熊正云,方贤文..基于概念漂移检测的数字孪生流程预测模型[J].计算机应用研究,2024,41(7):2039-2045,7.基金项目
国家自然科学基金资助项目(61572035) （61572035）
安徽省重点研究与开发计划资助项目(2022a05020005) （2022a05020005）
安徽省自然科学基金资助项目(水科学联合基金)(2308085US11) （水科学联合基金）
安徽理工大学研究生创新基金资助项目(2022CX2137) （2022CX2137）
