Transition-driven time prediction for business processes with cycles-Reference-Cited by-同舟云学术

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Transition-driven time prediction for business processes with cycles

Published:2022-12 Issue: Volume:209 Page:118238
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Cao Rui^ORCID,Zeng Qingtian^ORCID,Ni Weijian,Lu Faming,Zhou Changhong^ORCID,Guo Wenyan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference35 articles.

1. A vector-based classification approach for remaining time prediction in business processes;Aburomman;IEEE Access,2019

2. Queue-based features for dynamic waiting time prediction in emergency department;Benevento;Measuring Business Excellence,2019

3. An extended model for remaining time prediction in manufacturing systems using process mining;Choueiri;Journal of Manufacturing Systems,2020

4. Genetic algorithms for hyperparameter optimization in predictive business process monitoring;Di Francescomarino;Information Systems,2018

5. Predictive process monitoring methods: Which one suits me best?;Di Francescomarino,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extracting and Exploiting the Behavior Business Process Graph through Transition-Centric Event-Log data;2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1);2023-04-21

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