Please use this identifier to cite or link to this item: https://hdl.handle.net/10953/2087
Title: Visualization and Interpretation Tool for Expert Systems Based on Fuzzy Cognitive Maps
Authors: Garzón Casado, Álvaro
Cano Marchal, Pablo
Gómez Ortega, Juan
Gámez García, Javier
Abstract: This paper presents a python library that includes a toolkit with the aim of improving the interpretability of expert systems based on fuzzy cognitive maps through improvements in the visualization and representation of the graphs that can be drawn using the variables of the resulting models. The motivation for the development of the library arises from the need to improve the interpretability of the aforementioned expert systems, given that their multilayer and extracted from experts’ knowledge nature can make them very difficult to interpret even for the expert user. Throughout the paper, the reader will be introduced to the basic features of fuzzy logic and fuzzy cognitive maps, and the different developed tools will be defined and exemplified.
Keywords: Fuzzy cognitive maps
Expert systems
Interpretability
Issue Date: 2019
Publisher: IEEE
Citation: Á. Garzón Casado, P. Cano Marchal, J. Gómez Ortega and J. Gámez García, "Visualization and Interpretation Tool for Expert Systems Based on Fuzzy Cognitive Maps," in IEEE Access, vol. 7, pp. 6140-6150, 2019, doi: 10.1109/ACCESS.2018.2887355
Appears in Collections:DIEA-Artículos

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