Selection of a robust experimental design for the effective modeling of nonlinear systems using Genetic Programming

Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Volumn , Issue , 2013, Pages 287-292

  Garg, A ^a   Tai, K ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

experimental designs; full factorial design; genetic programming; latin hypercube sampling; response surface design

Indexed keywords

EVOLUTIONARY APPROACH; FULL FACTORIAL DESIGN; LATIN HYPERCUBE SAMPLING; OPTIMAL MODEL STRUCTURES; PRE-PROCESSING STEP; RESPONSE SURFACE DESIGNS; ROBUST EXPERIMENTAL DESIGNS; SYSTEM CHARACTERISTICS;

ARTIFICIAL INTELLIGENCE; DATA MINING; GENETIC PROGRAMMING; NONLINEAR SYSTEMS; STATISTICS; SURFACE PROPERTIES;

DESIGN OF EXPERIMENTS;

EID: 84885571970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIDM.2013.6597249     Document Type: Conference Paper

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