RT Journal Article
T1 MODELFY: A Model-driven Solution for Decision Making based on Fuzzy Information
A1 Castañeda, María
A1 García Merayo, María De Las Mercedes
A1 Boubeta-Puig, Juan
A1 Calvo, Iván
AB There exist areas, such as the disease prevention or inclement weather protocols, in which the analysis of the information based on strict protocols require a high level of rigor and security. In this situation, it would be desirable to apply formal methodologies that provide these features. In this scope, recently, it has been proposed a formalism, fuzzy automaton, that captures two relevant aspects for fuzzy information analysis: imprecision and uncertainty. However, the models should be designed by domain experts, who have the required knowledge for the design of the processes, but do not have the necessary technical knowledge. To address this limitation, this paper proposes MODELFY, a novel model-driven solution for designing a decision-making process based on fuzzy automata that allows users to abstract from technical complexities. With this goal in mind, we have developed a framework for fuzzy automaton model design based on a Domain- Specific Modeling Language (DSML) and a graphical editor. To improve the interoperability and functionality of this framework, it also includes a model-to-text transformation that translates the models designed by using the graphical editor into a format that can be used by a tool for data anal- ysis. The practical value of this proposal is also evaluated through a non-trivial medical protocol for detecting potential heart problems. The results confirm that MODELFY is useful for defining such a protocol in a user-friendly and rigorous manner, bringing fuzzy automata closer to domain experts.
PB Journal of Universal Computer Science
SN 0948-6968
SN 0948-695X
YR 2022
FD 2022-05-28
LK https://hdl.handle.net/20.500.14352/119485
UL https://hdl.handle.net/20.500.14352/119485
LA eng
NO Ministerio de Economía, Comercio y Empresa
NO Comunidad de Madrid
DS Docta Complutense
RD 26 feb 2026