This paper describes a different approach: using the genetic algorithm not only for finding the optimum of the given cost function, but for adapting an existing solution of the present problem to the new, modified problem. The genetic algorithm was extended to deal with the dynamic approximation problem: the time series were changed during the optimization process. |