International Journal of Man-Machine Studies
A fuzzy cognitive mapping analysis of the impacts of an eco-industrial park
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy cognitive map architectures for medical decision support systems
Applied Soft Computing
Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps
Information Sciences: an International Journal
Benchmarking main activation functions in fuzzy cognitive maps
Expert Systems with Applications: An International Journal
A new hybrid method using evolutionary algorithms to train Fuzzy Cognitive Maps
Applied Soft Computing
Expert Systems with Applications: An International Journal
Modeling complex systems using fuzzy cognitive maps
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
HICSS '13 Proceedings of the 2013 46th Hawaii International Conference on System Sciences
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Fuzzy cognitive mapping is commonly used as a participatory modelling technique whereby stakeholders create a semi-quantitative model of a system of interest. This model is often turned into an iterative map, which should (ideally) have a unique stable fixed point. Several methods of doing this have been used in the literature but little attention has been paid to differences in output such different approaches produce, or whether there is indeed a unique stable fixed point. In this paper, we seek to highlight and address some of these issues. In particular we state conditions under which the ordering of the variables at stable fixed points of the linear fuzzy cognitive map (iterated to) is unique. Also, we state a condition (and an explicit bound on a parameter) under which a sigmoidal fuzzy cognitive map is guaranteed to have a unique fixed point, which is stable. These generic results suggest ways to refine the methodology of fuzzy cognitive mapping. We highlight how they were used in an ongoing case study of the shift towards a bio-based economy in the Humber region of the UK.