Abstract
The aim of this paper is to provide a new class of Petri nets called parameterised fuzzy Petri nets. The new class extends the generalised fuzzy Petri nets by introducing two parameterised families of sums and products, which are supposed to function as substitute for the t-norms and s-norms. The power and the usefulness of this model on the base of parameterised fuzzy Petri nets application in the domain of train traffic control are presented. The new model is more flexible than the generalised one as in the former class the user has the chance to define the parameterised input/output operators. The proposed model can be used for knowledge representation and approximate reasoning in decision support systems.
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Suraj, Z. (2012). Parameterised Fuzzy Petri Nets for Approximate Reasoning in Decision Support Systems. In: Hassanien, A.E., Salem, AB.M., Ramadan, R., Kim, Th. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2012. Communications in Computer and Information Science, vol 322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35326-0_4
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DOI: https://doi.org/10.1007/978-3-642-35326-0_4
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