Optimal mapping from chromosome space to feature space for solving sequential pattern recognition problems

In this paper we present a method for modeling a genetic algorithm for a sequential pattern recognition problem. This genetic algorithm is shown to be useful in obtaining particular solutions; similarities between particular solutions give a general solution. Transition between chromosome space and feature space is done through relating genes to inputs, based on the discrete nature of both spaces.