کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4943036 | 1437619 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Run-time prediction of business process indicators using evolutionary decision rules
ترجمه فارسی عنوان
پیش بینی زمان اجرا شاخص های فرآیند کسب و کار با استفاده از قوانین تصمیم گیری تکاملی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
مدیریت فرایند کسب و کار، معدن فرایند، نظارت پیش بینی، شاخص فرآیند کسب و کار، الگوریتم تکاملی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Predictive monitoring of business processes is a challenging topic of process mining which is concerned with the prediction of process indicators of running process instances. The main value of predictive monitoring is to provide information in order to take proactive and corrective actions to improve process performance and mitigate risks in real time. In this paper, we present an approach for predictive monitoring based on the use of evolutionary algorithms. Our method provides a novel event window-based encoding and generates a set of decision rules for the run-time prediction of process indicators according to event log properties. These rules can be interpreted by users to extract further insight of the business processes while keeping a high level of accuracy. Furthermore, a full software stack consisting of a tool to support the training phase and a framework that enables the integration of run-time predictions with business process management systems, has been developed. Obtained results show the validity of our proposal for two large real-life datasets: BPI Challenge 2013 and IT Department of Andalusian Health Service (SAS).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 1-14
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 1-14
نویسندگان
Alfonso E. Márquez-Chamorro, Manuel Resinas, Antonio Ruiz-Cortés, Miguel Toro,