Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 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  - 10.2991/.2013.4
ID  - Napoles2013/10
ER  -