Abstract
Semantic graphs like fuzzy cognitive map (FCM) are known as powerful methodologies commonly used in control applications, as well as in relationship modeling. Besides, FCM is used as a systematic way for analyzing real-world problems with numerous known, partially known and unknown factors. This chapter discusses FCM application in relationship modeling context using some agile inference mechanisms. A sigmoid-based activation function is discussed with application in modeling hexapod locomotion gait. The activation algorithm is then added with a Hebbian weight training technique to enable automatic construction of FCMs. A numerical example case is included to show the performance of the developed model. The model is examined with perceptron learning rule as well. Finally a real-life example case is tested to evaluate the final model in terms of relationship modeling.
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Motlagh, O., Tang, S.H., Jafar, F.A., Khaksar, W. (2014). FCM Relationship Modeling for Engineering Systems. In: Papageorgiou, E. (eds) Fuzzy Cognitive Maps for Applied Sciences and Engineering. Intelligent Systems Reference Library, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39739-4_3
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DOI: https://doi.org/10.1007/978-3-642-39739-4_3
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