Genetic algorithm for selection of an optimum reduced set of input vector components: The algorithm starts with a random population in which each chromosome consists of a random distribution of enabled/disabled (on/off) input vector components denoted A
(where the number of components with "on" status remains fixed during evolution). This distribution is changed by mutation and cross-over. The fitness of each chromosome is evaluated by the inverse square RMSE. The selection process for each generation is performed by Roulette wheel selection where chromosomes are inherited with probabilities that correspond to their particular fitness.