References

  1. S.P. Borgatti, A. Mehra, D.J. Brass & G. Labianca (2009): Network Analysis in the Social Sciences. Science 323, pp. 892–5, doi:10.1126/science.1165821.
  2. Nicholas M. Gotts (2007): Resilience, Panarchy, and World-Systems Analysis. Ecology and Society 12(1).
  3. J. E. Hopcroft & R. M. Karp (1973): An n^5 / 2 algorithm for maximum matchings in bipartite graphs. SIAM J. Comput. 2, pp. 225–231, doi:10.1137/0202019.
  4. C. Knight (2013): Extending an FCM Using Control Nodes. Technical Report. University of Surrey.
  5. C. Knight, D.J.B. Lloyd & A. Penn (2014): Linear and Sigmoidal fuzzy cognitive maps: An analysis of fixed points. Applied Soft Computing 15, pp. 193–202, doi:10.1016/j.asoc.2013.10.030.
  6. B. Kosko (1986): Fuzzy Cognitive Maps. Int'l Journal of Man-Machine Studies 24, pp. 65–75, doi:10.1016/S0020-7373(86)80040-2.
  7. P.J. Krause, A. Razavi, S. Moschoyiannis & A. Marinos (2009): Stability and Complexity in Digital Ecosystems. In: IEEE DEST 2009, pp. 85–90, doi:10.1109/DEST.2009.5276757.
  8. C-T. Lin (1974): Structural Controllability. IEEE Trans. Autom. Contr. 19, pp. 201–208, doi:10.1109/TAC.1974.1100557.
  9. C.M Lin (2008): Using Fuzzy Cognitive Map for System Control. WSEAS Transactions on Systems 12(7), pp. 1504–1505.
  10. Y-Y. Liu, J-J. Slotine & A-L Barabasi (2011): Controllability of Complex Networks. Nature 473, pp. 167–173, doi:10.1038/nature10011.
  11. Y-Y. Liu, J-J. Slotine & A-L Barabasi (2011): Controllability of Complex Networks. Supplementary Information.
  12. R. M. May, S. A. Levin & G. Sugihara (2008): Complex Systems: Ecology for Bankers. Nature 451, pp. 893–895, doi:10.1038/451893a.
  13. E. Mitleton-Kelly (2003): Complex systems and evolutionary perpsectives on organisations: the application of complexity theory to organisations. Elsevier Science Ltd, Oxford, UK.
  14. U. Ozesmi & LS Ozesmi (2004): Ecological models based on people's knowledge: a multi-step fuzzy cognitive mapping approach. Ecological Modelling 15, pp. 43–64, doi:10.1016/j.ecolmodel.2003.10.027.
  15. A. Penn, C. Knight, D.J. Lloyd, D. Avitabile, K. Kok, F. Schiller, A. Woodward, A. Druckman & L. Basson (2013): Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region. PLOS ONE, doi:10.1371/journal.pone.0078319.t001.
  16. A. Penn (2016): Extending Participatory Fuzzy Cognitive Mapping with a Control Nodes Methodology: A Case Study of the Development of a Bio-based Economy in the Humber Region, UK. In: S. Gray, M. Paolisso & R. Jordan: Environmental Modeling with Stakeholders. Springer.
  17. S.R. Proulx, D.E.L. Promislkow & P.C. Philips (2005): Network Thinking in Ecology and Evolution. Trends in Ecology and Evolution 20, pp. 345–353, doi:10.1016/j.tree.2005.04.004.
  18. A. Razavi, S. Moschoyiannis & P.J. Krause (2009): An Open Digital Environment to support Business Ecosystems. Peer-to-Peer Networking and Applications 2(4), pp. 367–397, doi:10.1007/s12083-009-0039-5.
  19. M. Schneider, E. Shnaider, A. Kandel & G. Chew (1998): Automatic construction of FCMs. Fuzzy Sets and Systems 93, pp. 161–172, doi:10.1016/S0165-0114(96)00218-7.
  20. J-J. Slotine & W. Li (1991): Applied Nonlinar Control. Prentice Hall.
  21. LS Soler, K. Kok, G Camara & A. Veldkamp (2012): Using fuzzy cognitive maps to describe current system dunamics and develop land cover scenarios: a case study in the Brazilian Amazon. Journal of Land Use Science 7, pp. 149–175, doi:10.1080/1747423X.2010.542495.
  22. Dylan Young (2015): Carbon, Communities and Contestation. University of Leeds.
  23. W. Yu, G. Chen, M. Cao & J. Kurths (2010): Second-order consensus for multiagent systems with directed topologies and nonlinear dynamics. IEEE Trans. Syst. Man Cybern. B 40, pp. 881–891, doi:10.1109/TSMCB.2009.2031624.

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