Anuj Pratap Singh, V. Mani, Ranjan Ganguli¹

CMES-Computer Modeling in Engineering & Sciences, Vol.21, No.2, pp. 133-148, 2007, DOI:10.3970/cmes.2007.021.133

Abstract This paper investigates the use of Genetic Programming (GP) to create an approximate model for the non-linear relationship between flexural stiffness, length, mass per unit length and rotation speed associated with rotating beams and their natural frequencies. GP, a relatively new form of artificial intelligence, is derived from the Darwinian concept of evolution and genetics and it creates computer programs to solve problems by manipulating their tree structures. GP predicts the size and structural complexity of the empirical model by minimizing the mean square error at the specified points of input-output relationship dataset. This dataset is generated using a finite… More >

Selden B. Crary¹, Peter Cousseau², David Armstrong¹, David M. Woodcock³, Eva H. Mok¹, Olivier Dubochet⁴, Philippe Lerch⁴, Philippe Renaud²

CMES-Computer Modeling in Engineering & Sciences, Vol.1, No.1, pp. 127-140, 2000, DOI:10.3970/cmes.2000.001.127

Abstract We present a new and unique software capability for finding statistical optimal designs of deterministic experiments on continuous cuboidal regions. The objective function for the design optimization is the minimization of the expected integrated mean squared error of prediction of the metamodel that will be found, subsequent to the running of the computer simulations, using the best linear unbiased predictor (BLUP). The assumed response-model function includes an unknown, stochastic term, Z. We prove that this criterion, which we name I_Z-optimality, is equivalent to I-optimality for non-deterministic experiments, in the limit of zero correlations among the Z's for different inputs. An… More >