Name
Title | ||
|---|---|---|
Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation |
Abstract | ||
|---|---|---|
One of the problems that focus the research in the linguistic fuzzy modeling area is the trade-off between interpretability and accuracy. To deal with this problem, different approaches can be found in the literature. Recently, a new linguistic rule representation model was presented to perform a genetic lateral tuning of membership functions. It is based on the linguistic 2-tuples representation that allows the lateral displacement of a label considering an unique parameter. This way to work involves a reduction of the search space that eases the derivation of optimal models and therefore, improves the mentioned trade-off. Based on the 2-tuples rule representation, this work proposes a new method to obtain linguistic fuzzy systems by means of an evolutionary learning of the data base ap riori(number of labels and lateral dis- placements) and a simple rule generation method to quickly learn the associated rule base. Since this rule generation method is run from each data base definition generated by the evolutionary algorithm, its selection is an important aspect. In this work, we also propose two new ad hoc data-driven rule gener- ation methods, analyzing the influence of them and other rule generation methods in the proposed learn- ing approach. The developed algorithms will be tested considering two different real-world problems. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.ijar.2006.02.007 | International Journal of Approximate Reasoning |
Keywords | Field | DocType |
simple rule generation method,2-tuples representation,fuzzy rule-based systems,learning,associated rule base,genetic learning,linguistic fuzzy modeling area,genetic algorithms,rule generation method,linguistic 2-tuples representation,compact fuzzy rule,2-tuples linguistic representation,2-tuples rule representation,lateral displacement,new linguistic rule representation,interpretability–accuracy trade-off,linguistic fuzzy system,data base definition,fuzzy system,membership function,genetic algorithm,genetics,evolutionary algorithm,search space,association rule | Interpretability,Evolutionary algorithm,Tuple,A priori and a posteriori,Fuzzy logic,Artificial intelligence,Fuzzy control system,Linguistics,Membership function,Machine learning,Genetic algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
44 | 1 | International Journal of Approximate Reasoning |
Citations | PageRank | References |
67 | 1.91 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Alcalá | 1 | 1234 | 48.20 |
| J. Alcalá-Fdez | 2 | 2059 | 74.03 |
| Francisco Herrera | 3 | 27391 | 1168.49 |
| José Otero | 4 | 552 | 24.66 |