Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Multi-layered evolutionary system suitable to symbolic model regression
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
Application of symbolic regression on blast furnace and temper mill datasets
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
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The paper deals with symbolic regression of deterministic chaos systems using a GPA-ES system. A Lorenz attractor, Rossler attractor, Rabinovich-Fabrikant equations and a van der Pol oscillator are used as examples of deterministic chaos systems to demonstrate significant differences in the efficiency of the symbolic regression of systems described by equations of similar complexity. Within the paper, the source of this behavior is identified in presence of structures which are hard to be discovered during the evolutionary process due to the low probability of their occurrence in the initial population and by the low chance to produce them by standard evolutionary operators given by small probability to form them in a single step and low fitness function magnitudes of inter-steps when GPA tries to form them in more steps. This low magnitude of fitness function for particular solutions tends to eliminate them, thus increasing the number of needed evolutionary steps. As the solution of identified problems, modification of terminals and related crossover and mutation operators are suggested.