Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Autor: Renners, Ingo.

Publikováno v: LF.

Magdeburg, University, Diss., 2004.

Externí odkaz: http://diglib.uni-magdeburg.de/Dissertationen/2004/ingrenners.pdf
http://diglib.uni-magdeburg.de/Dissertationen/2004/ingrenners.htm
http://deposit.ddb.de/cgi-bin/dokserv?idn=974452351

An evolutionary approach to constraint-regularized learning

Autor: Hüllermeier, Eyke, Renners, Ingo, Grauel, Adolf

Publikováno v: Mathware & soft computing; 2004: Vol.: 11 Núm.: 2-3
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

The success of machine learning methods for inducing models from data crucially depends on the proper incorporation of background knowledge about the model to be learned. The idea of constraint-regularized learning is to em- ploy fuzzy set-based mode

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::720ee09939c5f92dcb3ea398b002d248
http://www.raco.cat/index.php/Mathware/article/view/84907