Name
Title | ||
|---|---|---|
Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework |
Abstract | ||
|---|---|---|
In this paper we propose a multi-objective evolutionary algorithm to generate Mamdani fuzzy rule-based systems with different good trade-offs between complexity and accuracy. The main novelty of the algorithm is that both rule base and granularity of the uniform partitions defined on the input and output variables are learned concurrently. To this aim, we introduce the concepts of virtual and concrete rule bases: the former is defined on linguistic variables, all partitioned with a fixed maximum number of fuzzy sets, while the latter takes into account, for each variable, a number of fuzzy sets as determined by the specific partition granularity of that variable. We exploit a chromosome composed of two parts, which codify the variables partition granularities, and the virtual rule base, respectively. Genetic operators manage virtual rule bases, whereas fitness evaluation relies on an appropriate mapping strategy between virtual and concrete rule bases. The algorithm has been tested on two real-world regression problems showing very promising results. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.ijar.2009.04.004 | Int. J. Approx. Reasoning |
Keywords | Field | DocType |
linguistic variable,mamdani fuzzy rule-based systems,fuzzy set,concurrently partition granularity,mamdani fuzzy system,rule base,multi-objective evolutionary algorithm,multi-objective evolutionary algorithms,variables partition granularity,mamdani fuzzy rule-based system,fixed maximum number,output variable,accuracy-interpretability trade-off,partition granularity learning,concrete rule base,multi-objective evolutionary framework,virtual rule base,rule based,fuzzy system,genetic operator | Evolutionary algorithm,Fuzzy logic,Fuzzy set,Artificial intelligence,Granularity,Fuzzy control system,Rule of inference,Machine learning,Mathematics,Genetic algorithm,Fuzzy rule | Journal |
Volume | Issue | ISSN |
50 | 7 | International Journal of Approximate Reasoning |
Citations | PageRank | References |
44 | 1.15 | 35 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michela Antonelli | 1 | 273 | 15.38 |
| Pietro Ducange | 2 | 566 | 27.63 |
| Beatrice Lazzerini | 3 | 715 | 45.56 |
| Francesco Marcelloni | 4 | 1404 | 91.43 |