On cosine fuzzy sets and uncertainty quantification
This paper presents a definition of a generalized cosine-based fuzzy set, its application into simulation problems and uncertainty quantification in order to cover both aleatoric and epistemic uncertainties commonly seen in non-probabilistic models. The proposed cosine fuzzy set is able to represent different shapes via a parameter b which operates as the power of a cosine-type function adding flexibility to its behavior. Some special cases, some of its properties and a random variate generation method are described and applied into three examples: a random variate example and uncertainty quantification for two benchmark functions.
Authors
- Roman Neruda (ORCID: https://orcid.org/0000-0003-2364-5357)
- Juan Carlos Figueroa–García (ORCID: https://orcid.org/0000-0001-5544-5937)
- German Jairo Hernandez-Perez (ORCID: https://orcid.org/0000-0001-9549-2316)
Institutions
- Czech Academy of Sciences (CZ)
- Universidad Distrital Francisco José de Caldas (CO)
- Universidad Nacional de Colombia (CO)
- Czech Academy of Sciences, Institute of Computer Science (CZ)
Publication Details
- Journal
- Engineering Applications of Artificial Intelligence
- Published
- 2024-09-10
- DOI
- https://doi.org/10.1016/j.engappai.2024.109241
- Citations
- 4
- Primary Topic
- Multi-Criteria Decision Making
- Type
- article
- Field-Weighted Citation Impact
- 1.96