TY - GEN
T1 - An evolutionary approach to identification problems with incomplete output data
AU - Imae, Joe
AU - Morita, Yasuhiko
AU - Zhai, Guisheng
AU - Kobayashi, Tomoaki
PY - 2008
Y1 - 2008
N2 - In this paper, we consider nonlinear system identification problems in the case where output data is incomplete. We propose an identification method based on an evolutionary algorithm, which is a fusion of a genetic algorithm (GA) and genetic programming (GP), and illustrate the effectiveness of the proposed method through a simulation and an experiment with a cart.
AB - In this paper, we consider nonlinear system identification problems in the case where output data is incomplete. We propose an identification method based on an evolutionary algorithm, which is a fusion of a genetic algorithm (GA) and genetic programming (GP), and illustrate the effectiveness of the proposed method through a simulation and an experiment with a cart.
KW - Evolutionary computation
KW - Genetic algorithm
KW - Genetic programming
KW - Incomplete output data
KW - Nonlinear system identification
UR - http://www.scopus.com/inward/record.url?scp=56749177317&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=56749177317&partnerID=8YFLogxK
U2 - 10.1109/SICE.2008.4655041
DO - 10.1109/SICE.2008.4655041
M3 - Conference contribution
AN - SCOPUS:56749177317
SN - 9784907764296
T3 - Proceedings of the SICE Annual Conference
SP - 2262
EP - 2265
BT - Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
T2 - SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Y2 - 20 August 2008 through 22 August 2008
ER -