Evolutionary Optimization of Case-Based Forecasting Algorithms in Chaotic Environments

The problem of dynamic adaptation prediction algorithms in chaotic environments based on identification the situations-analogs database retrospective observations is considered. Under conditions symmetrical and unsymmetrical dynamics, traditional computational schemes precedent turn out to be ineffective. In this regard, a analysis method evolutionary modeling proposed. Implementation scheme for processes as well are described.