Output sensitive discretization for genetic algorithm with migration
Sz. Kovács, G. J. Tóth, R. Der and A. Lõrincz
Neural Network World
6,
101--107
(1996)
Abstract
Approximation of unknown input-output mappings by optimizing approximating
functions is important for a number of practical applications. A
straightforward method involves dividing the whole input space into small
regions and finding the optimal approximating value within each. For such
a method to work well the way the input region is divided is very
important. In this paper we derive an algorithm that takes into account
both the distribution of the input points and how rapidly the mapping is
changing. The method is demonstrated on a simple function approximation
problem.
