Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support

Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery

Authors
Gonzalo Napoles, Isel Grau, Ricardo Pérez-García, Rafael Bello
Corresponding Author
Gonzalo Napoles
Available Online October 2013.
DOI
https://doi.org/10.2991/.2013.4How to use a DOI?
Keywords
FCM, modeling, simulation, learning, knowledge discovery
Abstract
In recent years Fuzzy Cognitive Maps (FCM) has be-come a useful Soft Computing technique for modeling and simulation. They are connectionist and recurrent structures involving concepts describing the system be-havior, and causal connections. This paper describes two abstract models based on Swarm Intelligence for learning parameters characterizing FCM, which is a central issue on this field. At the end, we obtain accurate maps, allow-ing the simulation of the system and also the extraction of relevant knowledge associated with underlying patterns.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
978-90-78677-86-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/.2013.4How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Gonzalo Napoles
AU  - Isel Grau
AU  - Ricardo Pérez-García
AU  - Rafael Bello
PY  - 2013/10
DA  - 2013/10
TI  - Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery
BT  - Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 27
EP  - 36
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.4
DO  - https://doi.org/10.2991/.2013.4
ID  - Napoles2013/10
ER  -