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Identification of Mechanical Behaviour by Genetic Programming Part II: Energy Formulation

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Ecole Polytechnique, 91128 Palaiseau, France, (1995)

Abstract

Goal is to build hyper-elastic 3-D models using statc experiments. Focuses on discovering local energy function using GP. Splits deep evolution (ie crossover and mutation) from surface evolution (parameter adjustment using random process like Evolution Strategies). Uses generational GPQuick. Crossover 0.3, mutation 0.5 and copy 0.2 Prepared to run to 1000 generations. Pop size 500. Fitness based on closeness of match both of GP function and also its derivative. (tentativly this seems to increase both accuracy and robustness) However results indicate GP is overfitting (due to single fitness case?)

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