Process Mining Techniques in Simulation Model Adequacy Assessment

被引:1
|
作者
Sitova, Irina [1 ]
Pecerska, Jelena [1 ]
机构
[1] Riga Tech Univ, Dept Modelling & Simulat, Riga, Latvia
来源
2019 60TH INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATION TECHNOLOGY AND MANAGEMENT SCIENCE OF RIGA TECHNICAL UNIVERSITY (ITMS) | 2019年
关键词
process mining; simulation model adequacy; simulation results analysis;
D O I
10.1109/itms47855.2019.8940672
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The research is carried out in the area of model adequacy assessment and analysis of simulation results. The aim of this research is to explore the applicability of process mining techniques for model verification and validation, and results analysis of discrete-event system simulation models. The adequacy assessment of the simulation model is the final stage of its development and has the objective to check the compliance of the model with its research objectives and to assess the reliability and statistical characteristics of the results obtained during the model experiments. In this paper the adequacy of the particular simulation model is checked for compliance with the real system from the point of view of the behaviour. The process mining is considered as a technique for simulated behaviour analysis. The simulation runs provided events lists for event log extraction. Further processing of event log resulted in positive objective conclusion on the investigated model behaviour adequacy, as well as outlined the potential direction to develop the objective adequacy assessment scheme for simulation models.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Combination of Process Mining and Simulation Techniques for Business Process Redesign: A Methodological Approach
    Aguirre, Santiago
    Parra, Carlos
    Alvarado, Jorge
    DATA-DRIVEN PROCESS DISCOVERY AND ANALYSIS, 2013, 162 : 24 - 43
  • [2] Teamwork Assessment in Collaborative Projects Through Process Mining Techniques
    Antonio Caballero-Hernandez, Juan
    Balderas, Antonio
    Palomo-Duarte, Manuel
    Delatorre, Pablo
    Reinoso, Antonio J.
    Manuel Dodero, Juan
    INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION, 2020, 36 (01) : 470 - 482
  • [3] Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification
    Kovalchuk, Sergey, V
    Funkner, Anastasia A.
    Metsker, Oleg G.
    Yakovlev, Aleksey N.
    JOURNAL OF BIOMEDICAL INFORMATICS, 2018, 82 : 128 - 142
  • [4] Redesigning business processes: a methodology based on simulation and process mining techniques
    Maruster, Laura
    van Beest, Nick R. T. P.
    KNOWLEDGE AND INFORMATION SYSTEMS, 2009, 21 (03) : 267 - 297
  • [5] The Use of Process Mining in Business Process Simulation Model ConstructionStructuring the Field
    Niels Martin
    Benoît Depaire
    An Caris
    Business & Information Systems Engineering, 2016, 58 : 73 - 87
  • [6] Redesigning business processes: a methodology based on simulation and process mining techniques
    Laura Măruşter
    Nick R. T. P. van Beest
    Knowledge and Information Systems, 2009, 21 : 267 - 297
  • [7] The Use of Process Mining in Business Process Simulation Model Construction Structuring the Field
    Martin, Niels
    Depaire, Benoit
    Caris, An
    BUSINESS & INFORMATION SYSTEMS ENGINEERING, 2016, 58 (01) : 73 - 87
  • [8] Towards an Automated Business Process Model Risk Assessment: A Process Mining Approach
    Dedousis, Panagiotis
    Raptaki, Melina
    Stergiopoulos, George
    Gritzalis, Dimitris
    SECRYPT : PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON SECURITY AND CRYPTOGRAPHY, 2022, : 35 - 46
  • [9] Applying Process Mining Techniques to Learning Management Systems for Educational Process Model Discovery and Analysis
    Etinger, Darko
    Orehovacki, Tihomir
    Babic, Snjezana
    INTELLIGENT HUMAN SYSTEMS INTEGRATION, IHSI 2018, 2018, 722 : 420 - 425
  • [10] Applying process mining techniques in software process appraisals
    Valle, Arthur M.
    Santos, Eduardo A. P.
    Loures, Eduardo R.
    INFORMATION AND SOFTWARE TECHNOLOGY, 2017, 87 : 19 - 31