A preliminary study to apply the Quine McCluskey algorithm for fuzzy rule base minimization
Leonardo Jara, Antonio González, Raúl Pérez · 2020
The Fuzzy Rule-Based Classification Systems (FR-BCS) are classification models that use fuzzy rules to represent knowledge. FBRCS are popular today, with numerous applications and studies of their behavior and efficiency. This work is dedicated to studying a method that allows the minimization of FBRCS generated by the Chi Algorithm, using the Quine-McCluskey method so that the number of generated rules can be reduced, without greatly altering the accuracy, thus improving the simplicity of the model.