@inproceedings{5844b9467a55421eb27a4bd83d316306,
title = "Risk Assessment Modeling Based on a Graded Fuzzy Concept Lattice",
abstract = "Fuzzy concept analysis is a well developed field of mathematics with many useful applications in various {\textquotedblleft}real-world{\textquotedblright} problems. On the other hand, while different methods based on fuzzy logic, for example, fuzzy implication systems, are successfully used in the risk assessment based on expert opinion, we are not aware of any work in which the apparatus of fuzzy concept lattices would be used in the study of problems related to risk analysis. The main purpose of this article is to analyze the prospects for using graded fuzzy concept lattices as the basis for a risk assessment model. To make a paper self-contained, we provide all the necessary information concerning fuzzy concept lattices and their graded version. Theoretical models are further considered in the analysis of pandemic scenario which provides an insight into practical modeling of risk management processes and assessment of particular risks.",
keywords = "Fuzzy context, Fuzzy preconcept, Gradation of fuzzy preconcept lattices, Graded fuzzy concept lattice, Pandemic scenario, Risk assessment, Risk factors",
author = "Māris Krastiņ{\v s} and Ingrida Uljane and Alexander {\v S}ostak",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Joint Conference on Computational Intelligence, IJCCI 2020 and 2021 ; Conference date: 25-10-2021 Through 27-10-2021",
year = "2023",
doi = "10.1007/978-3-031-46221-4\_7",
language = "English",
isbn = "9783031462207",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "144--162",
editor = "Jonathan Garibaldi and Christian Wagner and Thomas B{\"a}ck and Hak-Keung Lam and Marie Cottrell and Kurosh Madani and Kevin Warwick",
booktitle = "Computational Intelligence",
address = "Germany",
}