The kinetic evolutionary modeling of complex systems of chemical reactions

To overcome the drawbacks of most available methods for kinetic analysis, this paper proposes a hybrid evolutionary modeling algorithm called HEMA to build kinetic models of systems of ordinary differential equations (ODEs) automatically for complex systems of chemical reactions. The main idea of the 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 is employed to optimize its parameters. The experimental results of two chemical reaction systems show that by running the HEMA, the computer can discover the kinetic models automatically which are appropriate for describing the kinetic characteristics of the reacting systems. Those models can not only fit the kinetic data very well, but also give good predictions. (C) 1999 Elsevier Science Ltd. All rights reserved.