Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery
Gonzalo Napoles, Isel Grau, Ricardo Pérez-García, Rafael Bello
Available Online October 2013.
- https://doi.org/10.2991/.2013.4How to use a DOI?
- FCM, modeling, simulation, learning, knowledge discovery
- 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.
- 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 -