TY - CHAP
T1 - Using genetic programming in nonlinear model identification
AU - Winkler, Stephan
AU - Affenzeller, Michael
AU - Kronberger, Gabriel
AU - Kommenda, Michael
AU - Wagner, Stefan
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - 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 R&D 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.
AB - 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 R&D 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.
UR - http://www.scopus.com/inward/record.url?scp=84855902804&partnerID=8YFLogxK
U2 - 10.1007/978-1-4471-2221-0_6
DO - 10.1007/978-1-4471-2221-0_6
M3 - Chapter
SN - 9781447122203
T3 - Lecture Notes in Control and Information Sciences
SP - 89
EP - 109
BT - Identification for Automotive Systems
A2 - Alberer, Daniel
A2 - del Re, Luigi
A2 - Hjalmarsson, Hakan
PB - Springer
T2 - Workshop on Identification in Automotive
Y2 - 15 July 2010 through 16 July 2010
ER -