Using Genetic Programming in Nonlinear Model Identification

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InCollection{1793,

• author = "Stephan M. Winkler and Michael Affenzeller and Stefan Wagner and Gabriel K. Kronberger and Michael Kommenda",
• title = "Using Genetic Programming in Nonlinear Model Identification",
• booktitle = "Workshop on Identification in Automotive 2010",
• publisher = "Springer",
• year = "2010",
• editor = "Daniel Alberer and Hakan Hjalmarsson and Luigi {del Re}",
• volume = "418",
• series = "Lecture Notes in Control and Information Sciences",
• chapter = "6",
• pages = "89--109",
• address = "Linz, Austria",
• month = jul,
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4471-2221-0",
• URL = "https://link.springer.com/chapter/10.1007/978-1-4471-2221-0_6",
• DOI = "doi:10.1007/978-1-4471-2221-0_6",
• abstract = "In this paper we summarize the use of genetic programming (GP) in nonlinear system identification: After giving a short introduction to evolutionary computation and genetic algorithms, we describe the basic principles of genetic programming and how it is used for data based identification of nonlinear mathematical models. Furthermore, we summarize projects in which we have successfully applied GP in Research and Development projects in the last years; we also give a summary of several algorithmic enhancements that have been successfully researched in the last years (including offspring selection, on-line and sliding window GP, operators for monitoring genetic process dynamics, and the design of cooperative evolutionary data mining agents). A short description of HeuristicLab (HL), the optimization framework developed by the HEAL research group, and the use of the GP implementations in HL are given in the appendix of this paper.",
• notes = "Published 2012? LNCIS, volume 418",

}

Genetic Programming entries for Stephan M Winkler Michael Affenzeller Stefan Wagner Gabriel Kronberger Michael Kommenda

Citations