A Genetic Hybrid For Critical Heat Flux Function Approximation

Function approximation is the problem of nding a function that best explains the relationship between independent variables and a dependent variable. We propose a genetic hybrid for the critical heat ux function approximation which critically a ects the performance of nuclear plants. The problem is represented for genetic algorithm in a way that exploits the relationships between parameters. The experimental result signi cantly improved the existing function at KAERI (Korea Atomic Energy Research Institute). The framework is not just for the tested problem; it is believed to be applicable to other function approximation problems.