To overcome the drawbacks of most available methods for kinetic analysis, t
his paper proposes a hybrid evolutionary modeling algorithm called HEMA to
build kinetic models of systems of ordinary differential equations (ODEs) a
utomatically for complex systems of chemical reactions. The main idea of th
e algorithm is to embed a genetic algorithm (GA) into genetic programming (
GP) where GP is employed to optimize the structure of a model, while a GA i
s employed to optimize its parameters. The experimental results of two chem
ical reaction systems show that by running the HEMA, the computer can disco
ver the kinetic models automatically which are appropriate for describing t
he kinetic characteristics of the reacting systems. Those models can not on
ly fit the kinetic data very well, but also give good predictions. (C) 1999
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