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Using multilayer neural networks to estimate the parameters of the nonlinear Baret model

Enăchescu C., Constantinescu A.

Biocybernetics and Biomedical Engineering

2007

Vol. 27, no. 3

95-111

The complexity of the nonlinear models with random parameters doesn't generally allow to resolve in an easy way the parameters estimation problem. In this paper we design and use a multilayer neural network (MLNN) for the parameters estimation. We deal with the Baret model for the temporal evolution of the leaf area index (LAI).

Spatial localization of the error of constitutive law for the identification of defects in elastic bodies

Bui H., Constantinescu A.

Archives of Mechanics

2000

Vol. 52, nr 4-5

511-522

The error of constitutive law (ECL) is a cost functional currently used in inverse problems for identifying interior distribution of coefficients of partial differential equations from overspecified boundary conditions. In previous works, different authors have shown that the ECL enables a good spatial localization of the perturbations of the coefficients. The purpose of this paper is to justify this spatial localization property. The result is obtained for the elliptic equations of elasticity using boundary integral representations of the solutions and comparing the linear and the perturbed solution of the problem.