Genetic programming as an analytical tool for non-linear dielectric spectroscopy

By modelling the non-linear effects of membranous enzymes on an applied osc illating electromagnetic field using supervised multivariate analysis metho ds, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms, The use of Genetic Programming (GP) for the multivari ate analysis of NLDS data recorded from yeast fermentations is discussed, a nd GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods , both in terms of the precision of the predictions and their interpretabil ity. (C) 1999 Elsevier Science S.A. All rights reserved.