Abstract
The aim of this research is to automatically tuning a good fuzzy partition, i.e. determine the number of classes of each system variable, in the context of the Fuzzy Inductive Reasoning (FIR) methodology. FIR is an inductive methodology for modelling and simulate those systems from which no previous structural knowledge is available. The first step of FIR methodology is the fuzzification process that converts quantitative variables into fuzzy qualitative variables. In this process it is necessary to define the number of classes into which each variable is going to be discretized. In this paper an algorithm based on simulated annealing is developed to suggest a good partition in an automatic way. The proposed algorithm is applied to an environmental system.
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© 2003 Springer-Verlag Berlin Heidelberg
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Nebot, A. (2003). Automatic Tuning of Fuzzy Partitions in Inductive Reasoning. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds) Progress in Pattern Recognition, Speech and Image Analysis. CIARP 2003. Lecture Notes in Computer Science, vol 2905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24586-5_68
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DOI: https://doi.org/10.1007/978-3-540-24586-5_68
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