Modeling of inference systems based on the fuzzy repertory table technique. An experimental study
DOI:
https://doi.org/10.30973/progmat/2020.12.3/3Keywords:
inference rules, fuzzy logic, knowledge representationAbstract
Fuzzy Inference Systems (FIS) allow modeling complex processes where their main characteristic is the uncertainty or imprecision of the values. This type of system employs collections of “If-Then” rules that use linguistic labels to represent concepts that cannot have a precise quantitative analysis. This article presents a tool for the development of Fuzzy Inference Systems using the Fuzzy Repertory Table, a technique originated in the area of Psychology for the representation of knowledge that incorporates aspects of Fuzzy Logic. Given a set of examples, a set of fuzzy domains and their linguistic labels, the tool generates a multilevel fuzzy classification model, that is, fuzzy rules. These Fuzzy Inference Systems are of the MISO type (multiple-in, simple-out), that is, sets of fuzzy rules with several input variables and one output variable. The tool allows the user to develop, evaluate and use the fuzzy rules that model a process. A case study is presented that validates the technique and the developed tool. The results obtained allow us to corroborate the effectiveness of the system modeling tool using the Fuzzy RepertoryTable technique.
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