Statistical inverse analysis based on genetic algorithm and principal component analysis: Method and developments using synthetic data Export

@article{citeulike:5283535, abstract = {This study concerns the identification of parameters of soil constitutive models from geotechnical measurements by inverse analysis. To deal with the non-uniqueness of the solution, the inverse analysis is based on a genetic algorithm (GA) optimization process. For a given uncertainty on the measurements, the GA identifies a set of solutions. A statistical method based on a principal component analysis (PCA) is, then, proposed to evaluate the representativeness of this set. It is shown that this representativeness is controlled by the GA population size for which an optimal value can be defined. The PCA also gives a first-order approximation of the solution set of the inverse problem as an ellipsoid. These developments are first made on a synthetic excavation problem and on a pressuremeter test. Some experimental applications are, then, studied in a companion paper, to show the reliability of the method. Copyright {\copyright} 2009 John Wiley \& Sons, Ltd.}, address = {Laboratoire 'Sols, Solides, Structures-Risques', Universit\'{e} Joseph Fourier-Grenoble 1, CNRS INPG UJF, UMR 5521, BP 53, 38041 Grenoble cedex 9, France}, author = {Levasseur, S. and Malecot, Y. and Boulon, M. and Flavigny, E.}, citeulike-article-id = {5283535}, citeulike-linkout-0 = {http://dx.doi.org/10.1002/nag.776}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/122206601/ABSTRACT}, doi = {10.1002/nag.776}, issn = {1096-9853}, journal = {International Journal for Numerical and Analytical Methods in Geomechanics}, keywords = {microplane}, number = {12}, pages = {1485--1511}, posted-at = {2009-07-27 19:54:06}, priority = {2}, title = {Statistical inverse analysis based on genetic algorithm and principal component analysis: Method and developments using synthetic data}, url = {http://dx.doi.org/10.1002/nag.776}, volume = {33}, year = {2009} }

TY - JOUR ID - citeulike:5283535 L3 - citeulike-article-id:5283535 N2 - This study concerns the identification of parameters of soil constitutive models from geotechnical measurements by inverse analysis. To deal with the non-uniqueness of the solution, the inverse analysis is based on a genetic algorithm (GA) optimization process. For a given uncertainty on the measurements, the GA identifies a set of solutions. A statistical method based on a principal component analysis (PCA) is, then, proposed to evaluate the representativeness of this set. It is shown that this representativeness is controlled by the GA population size for which an optimal value can be defined. The PCA also gives a first-order approximation of the solution set of the inverse problem as an ellipsoid. These developments are first made on a synthetic excavation problem and on a pressuremeter test. Some experimental applications are, then, studied in a companion paper, to show the reliability of the method. Copyright © 2009 John Wiley & Sons, Ltd. IS - 12 JF - International Journal for Numerical and Analytical Methods in Geomechanics SN - 1096-9853 AD - Laboratoire 'Sols, Solides, Structures-Risques', Université Joseph Fourier-Grenoble 1, CNRS INPG UJF, UMR 5521, BP 53, 38041 Grenoble cedex 9, France EP - 1511 TI - Statistical inverse analysis based on genetic algorithm and principal component analysis: Method and developments using synthetic data VL - 33 SP - 1485 KW - microplane AU - Levasseur, S AU - Malecot, Y AU - Boulon, M AU - Flavigny, E PY - 2009/// UR - http://dx.doi.org/10.1002/nag.776 ER -