International Journal of Man-Machine Studies
Hidden patterns in combined and adaptive knowledge networks
International Journal of Approximate Reasoning
Cognitive mapping and certainty neuron fuzzy cognitive maps
Information Sciences: an International Journal
Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links
International Journal of Human-Computer Studies
Fuzzy Cognitive Maps in modeling supervisory control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy cognitive map architectures for medical decision support systems
Applied Soft Computing
Benchmarking main activation functions in fuzzy cognitive maps
Expert Systems with Applications: An International Journal
Using fuzzy cognitive map for system control
WSEAS TRANSACTIONS on SYSTEMS
Medical Decision Making through Fuzzy Computational Intelligent Approaches
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Risk Analysis Using Extended Fuzzy Cognitive Maps
ICICCI '10 Proceedings of the 2010 International Conference on Intelligent Computing and Cognitive Informatics
Structural damage detection using fuzzy cognitive maps and Hebbian learning
Applied Soft Computing
Intuitionistic Fuzzy Cognitive Maps for Medical Decision Making
IEEE Transactions on Information Technology in Biomedicine
Numerical and Linguistic Prediction of Time Series With the Use of Fuzzy Cognitive Maps
IEEE Transactions on Fuzzy Systems
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Fuzzy Cognitive Maps is an important representation tool that has the ability to model complicated systems. Based on linear influence relations between concepts, FCMs can be trained to lead a system to a desired state. This work proposes a generalized flexible nonlinear function as an alternative way of estimating that influence. Its adjustable character offers the ability to lead a FCM into a large set of different equilibrium states, where the conventional approach constitutes only one instance. Experimental studies present the properties of the proposed methodology in two benchmarks and other synthetic data. The examination of a system under different considerations of influence offers a more complete understanding of a system behavior.