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Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points

Knight, CJK, Penn, AS and Lloyd, DJB (2014) Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points Applied Soft Computing Journal, 15. pp. 193-202.

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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. © 2013 Elsevier B.V. All rights reserved.

Item Type: Article
Divisions : Surrey research (other units)
Authors : Knight, CJK, Penn, AS and Lloyd, DJB
Date : February 2014
DOI : 10.1016/j.asoc.2013.10.030
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 15:29
Last Modified : 24 Jan 2020 12:17

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