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A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development
Volume 32, Issue 1 (2021), pp. 85–118
Pub. online: 29 January 2021      Type: Research Article      Open accessOpen Access
Received
1 September 2020
Accepted
1 January 2021
Published
29 January 2021

Abstract

The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in fuzzy inference systems (FIS) development. However, researchers highlight different challenges and issues of this FIS development because of its complexity. This paper evaluates the current state of the art of FIS development complexity issues in Computer Science, Software Engineering and Information Systems, specifically: 1) What complexity issues exist in the context of developing FIS? 2) Is it possible to systematize existing solutions of identified complexity issues? We have conducted a hybrid systematic literature review combined with a systematic mapping study that includes keyword map to address these questions. This review has identified the main FIS development complexity issues that practitioners should consider when developing FIS. The paper also proposes a framework of complexity issues and their possible solutions in FIS development.

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Biographies

Kalibatienė Diana
diana.kalibatiene@vilniustech.lt

D. Kalibatienė is a full-time professor at the Department of Information Systems in Vilnius Gediminas Technical University (VilniusTECH). She received her doctoral degree in technological sciences, informatics engineering (PhD) in 2009 (the topic of doctoral dissertation is Ontology-Based Development of Domain Rules), and received the assoc. prof. degree in 2013. She is a co-author of more than 40 research papers and one book (Advanced Databases) in Computer Sciences. Her research interests include business rules and ontology-based information system development and conceptual modelling; knowledge-based multi-criteria dynamic business process modelling and simulation; multi-criteria decision-making method application in different fields; fuzzy theory application in quality planning and prediction.

She delivered lectures at Palermo University (Sicily, Italy), University of La Laguna (Tenerife), and University of Rousse (Bulgaria). She is supervising three doctoral students. She participated in the High Technology Development Program Project “Business Rules Solutions for Information Systems Development” (VeTIS). She is a member of the European Committee and Lithuanian Government supported SOCRATES/ERASMUS Thematic Network project “Doctoral Education in Computing” (ETN DEC), “Teaching, Research, Innovation in Computing Education” (ETN TRICE) and “Future Education and Training in Computing: How to Support Learning at Anytime Anywhere” (ETN FETCH). She participated in preparing the bachelor study programme “Business Information Systems” (now “Information Systems”) in 2010; and the bachelor study programme “Software Engineering” in 2012. Since 2019, she is a chair of the Study Program Committee of the “Information Systems Software Engineering” master study programme. Also, she is a member of the Study Program Committee of the bachelor study programmes “Information Systems” and “Software Engineering”.

Miliauskaitė Jolanta
jolanta.miliauskaite@mif.vu.lt

J. Miliauskaitė is a junior researcher at Vilnius University (Lithuania) Institute of Data Science and Digital Technologies Department of Cyber-Social Systems Engineering Group. She defended her a PhD in technological sciences, informatics engineering at Vilnius University (2015) on the topic A Fuzzy Inference-Based Approach to Planning Quality of Enterprise Business Services. Her research interests include enterprise business services, service-oriented enterprise systems, web service composition, quality of service modelling and evaluation in service-oriented enterprise systems. She is a co-author of research papers in the field of computer sciences. She is a lecturer at Vilnius University Faculty of Mathematics and Informatics and Vilnius Gediminas Technical University (Lithuania) Faculty of Fundamental Sciences Department of Information Systems. She participated in the project of EU Structural Funds “Theoretical and Engineering Aspects of E-Service Technology Development and Application in High-Performance Computing Platforms”. She is a member of organising committee of the International Baltic Conference on Databases and Information Systems (Baltic DB&IS 2012, Baltic DB&IS 2018). She is a member of Lithuanian Computer Society (LIKS).


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Keywords
membership function fuzzy rule fuzzy inference system issue limitation complexity systematic literature review systematic mapping

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