Abstract
In this research a genetic fuzzy system (GFS) is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR) methodology and the Linguistic Rule FIR (LR-FIR) algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR) models and decision support (LR-FIR) models. The GFS is evaluated in an e-learning context.
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Nebot, À., Mugica, F., Castro, F. et al. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling. Int J Comput Intell Syst 5, 387–402 (2012). https://doi.org/10.1080/18756891.2012.685328
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DOI: https://doi.org/10.1080/18756891.2012.685328