Abstract
A technique for Fuzzy Cognitive Maps learning, which is based on the minimization of a properly defined objective function using the Particle Swarm Optimization algorithm, is presented. The workings of the technique are illustrated on an industrial process control problem. The obtained results support the claim that swarm intelligence algorithms can be a valuable tool for Fuzzy Cognitive Maps learning, alleviating deficiencies of Fuzzy Cognitive Maps, and controlling the system's convergence.
Cite
CITATION STYLE
Papageorgiou, E. I., Parsopoulos, K. E., Groumpos, P. P., & Vrahatis, M. N. (2004). Fuzzy cognitive maps learning through swarm intelligence. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3070, pp. 344–349). Springer Verlag. https://doi.org/10.1007/978-3-540-24844-6_49
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
