References
- Axelrod, R. (1976). Structure of Decision: The Cognitive Maps of Political Elites, Princeton University Press, Princeton, NJ.
- Bartczuk, Ł., Przybył, A. and Cpałka, K. (2016). A new approach to nonlinear modelling of dynamic systems based on fuzzy rules, International Journal of Applied Mathematics and Computer Science26(3): 603–621, DOI: 10.1515/amcs-2016-0042.10.1515/amcs-2016-0042
- Boutalis, Y., Kottas, T.L. and Christodoulou, M. (2009). Adaptive estimation of fuzzy cognitive maps with proven stability and parameter convergence, IEEE Transactions on Fuzzy Systems17(4): 874–889.
- Buruzs, A., Hatwágner, M.F. and Kóczy, L.T. (2015). Expert-based method of integrated waste management systems for developing fuzzy cognitive map, in Q. Zhu and A. Azar (Eds), Complex System Modelling and Control Through Intelligent Soft Computations, Springer, Cham, pp. 111–137.
- Busemeyer, J.R. (2001). Dynamic decision making, in N.J. Smelser and P.B. Baltes (Eds), International Encyclopedia of the Social & Behavioral Sciences, Elsevier, New York, NY pp. 3903–3908.
- Carlsson, C. and Fullér, R. (2011). Possibility for Decision: A Possibilistic Approach to Real Life Decisions, Studies in Fuzziness and Soft Computing Series, Vol. 270/2011, Springer Publishing Company, Berlin/Heidelberg.
- Carvalho, J.P. (2013). On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences, Fuzzy Sets and Systems214: 6–19.
- Felix, G., Nápoles, G., Falcon, R., Froelich, W., Vanhoof, K. and Bello, R. (2017). A review on methods and software for fuzzy cognitive maps, Artificial Intelligence Review2017: 1–31.
- Ferreira, F.A., Ferreira, J.J., Fernandes, C.I., Meidut˙e-Kavaliauskien˙e, I. and Jalali, M.S. (2017). Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps, Technological and Economic Development of Economy23(6): 860–876.
- Harmati, I.Á., Hatwágner, M.F. and Kóczy, L.T. (2018). On the existence and uniqueness of fixed points of fuzzy cognitive maps, in J. Medina et al. (Eds), Information Processing and Management of Uncertainty in Knowledge-Based Systems: Theory and Foundations, Springer International Publishing, Cham, pp. 490–500.
- Harmati, I.Á. and Kóczy, L.T. (2018). On the convergence of fuzzy grey cognitive maps, in P. Kulczycki et al. (Eds), Contemporary Computational Science, AGH-UCT Press, Cracow, p. 139.
- Harmati, I.Á. and Kóczy, L.T. (2019). On the convergence of fuzzy grey cognitive maps, in P. Kulczycki et al. (Eds), Information Technology, Systems Research and Computational Physics, Advances in Intelligent Systems and Computing, Springer, Cham, pp. 74–84.
- Knight, C.J., Lloyd, D.J. and Penn, A.S. (2014). Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points, Applied Soft Computing15: 193–202.
- Kosko, B. (1986). Fuzzy cognitive maps, International Journal of Man-Machine Studies24(1): 65–75.
- Liu, S. and Lin, Y. (2006). Grey Information: Theory and Practical Applications, Springer Science & Business Media, London.
- Lorenz, S., Martinez-Fernández, V., Alonso, C., Mosselman, E., de Jalón, D.G., del Tánago, M.G., Belletti, B., Hendriks, D. and Wolter, C. (2016). Fuzzy cognitive mapping for predicting hydromorphological responses to multiple pressures in rivers, Journal of Applied Ecology53(2): 559–566.
- Nápoles, G., Papageorgiou, E., Bello, R. and Vanhoof, K. (2016). On the convergence of sigmoid fuzzy cognitive maps, Information Sciences349–350: 154–171.
- Nápoles, G., Papageorgiou, E., Bello, R. and Vanhoof, K. (2017). Learning and convergence of fuzzy cognitive maps used in pattern recognition, Neural Processing Letters45(2): 431–444.
- Papageorgiou, E.I. and Salmeron, J.L. (2012). Learning fuzzy grey cognitive maps using nonlinear Hebbian-based approach, International Journal of Approximate Reasoning53(1): 54–65.
- Papageorgiou, E.I. and Salmeron, J.L. (2013). A review of fuzzy cognitive maps research during the last decade, IEEE Transactions on Fuzzy Systems21(1): 66–79.
- Papageorgiou, E.I. and Salmeron, J.L. (2014). Methods and algorithms for fuzzy cognitive map-based modeling, in E. Papageorgiou (Ed.), Fuzzy Cognitive Maps for Applied Sciences and Engineering, Springer, Berlin/Heidelberg, pp. 1–29.
- Salmeron, J.L. (2010). Modelling grey uncertainty with fuzzy grey cognitive maps, Expert Systems with Applications37(12): 7581–7588.
- Salmeron, J.L. and Gutierrez, E. (2012). Fuzzy grey cognitive maps in reliability engineering, Applied Soft Computing12(12): 3818–3824.
- Salmeron, J.L. and Papageorgiou, E.I. (2012). A fuzzy grey cognitive maps-based decision support system for radiotherapy treatment planning, Knowledge-Based Systems30: 151–160.
- Smoczek, J. (2013). Evolutionary optimization of interval mathematics-based design of a TSK fuzzy controller for anti-sway crane control, International Journal of Applied Mathematics and Computer Science23(4): 749–759, DOI: 10.2478/amcs-2013-0056.10.2478/amcs-2013-0056
- Stylios, C.D. and Groumpos, P.P. (2004). Modeling complex systems using fuzzy cognitive maps, IEEE Transactions on Systems, Man, and Cybernetics A: Systems and Humans34(1): 155–162.
- Tsadiras, A.K. (2008). Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps, Information Sciences178(20): 3880–3894.
- Vidhya, R. and Hepzibah, R.I. (2017). A comparative study on interval arithmetic operations with intuitionistic fuzzy numbers for solving an intuitionistic fuzzy multi-objective linear programming problem, International Journal of Applied Mathematics and Computer Science27(3): 563–573, DOI: 10.1515/amcs-2017-0040.10.1515/amcs-2017-0040
- Zanon, L.G. and Carpinetti, L.C.R. (2018). Fuzzy cognitive maps and grey systems theory in the supply chain management context: A literature review and a research proposal, 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Rio de Janerio, Brazil, pp. 1554–1561.
- Ziv, G., Watson, E., Young, D., Howard, D.C., Larcom, S.T. and Tanentzap, A.J. (2018). The potential impact of Brexit on the energy, water and food nexus in the UK: A fuzzy cognitive mapping approach, Applied Energy210: 487–498.