Information-Dependent Switching of Identification Criteria in a Genetic Programming System for System Identification

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{eurogp06:BuchsbaumVossner,

• author = "Thomas Buchsbaum and Siegfried V{\"o}ssner",
• title = "Information-Dependent Switching of Identification Criteria in a Genetic Programming System for System Identification",
• editor = "Pierre Collet and Marco Tomassini and Marc Ebner and Steven Gustafson and Anik\'o Ek\'art",
• booktitle = "Proceedings of the 9th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3905",
• year = "2006",
• address = "Budapest, Hungary",
• month = "10-12 " # apr,
• organisation = "EvoNet",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-33143-3",
• pages = "300--309",
• DOI = "doi:10.1007/11729976_27",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• abstract = "Genetic Programming (GP) can be used to identify the nonlinear differential equations of dynamical systems. If, however, the fitness function is chosen in a classical way, the optimisation will not work very well. In this article, we explain the reasons for the failure of the GP approach and present a solution strategy for improving performance. Using more than one identification criterion (fitness function) and switching based on the information content of the data enable standard GP algorithms to find better solutions in shorter times. A computational example illustrates that identification criteria switching has a bigger influence on the results than the choice of the GP parameters has.",
• notes = "Part of \cite{collet:2006:GP} EuroGP'2006 held in conjunction with EvoCOP2006 and EvoWorkshops2006",

}

Genetic Programming entries for Thomas Buchsbaum Siegfried Vossner

Citations