Name
Abstract | ||
|---|---|---|
System identification is used to identify relevant input-output space relations. In this article the relations are used to model a descriptive Takagi-Sugeno fuzzy system. Basic terms of system identification, fuzzy systems and evolutionary computation are briefly reviewed. These concepts are used to present the implementation of an evolutionary algorithm which identifies (sub)optimal descriptive Takagi-Sugeno fuzzy systems according to given data. The proposed evolutionary algorithm is tested on the well known gas furnace data set and results are presented. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-45231-7_44 | ADVANCES IN INTELLIGENT DATA ANALYSIS V |
Keywords | Field | DocType |
fuzzy system,evolutionary computing,evolutionary algorithm,input output,system identification | Neuro-fuzzy,Fuzzy classification,Evolutionary algorithm,Fuzzy set operations,Computer science,Fuzzy logic,Evolutionary computation,Artificial intelligence,Fuzzy control system,System identification | Conference |
Volume | ISSN | Citations |
2810 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ingo Renners | 1 | 7 | 3.03 |
| Adolf Grauel | 2 | 34 | 9.56 |