HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Estrutura de propriedade e de controle das empresas de capital aberto no Brasil

This paper has as its main objective to measure the magnitude of deviations between control rights and cash-flow rights for the ultimate shareholder with the largest voting rights of limited liability companies in Brazil. Furthermore, it pinpoints how these discrepancies are generated, evaluating the relative importance of the issuance of preferred stocks with no voting rights, pyramidal arrangements of ownership, and cross-shareholdings. The data set embraces 602 companies that in 2001 complied with the mandatory requirement of filing to the CVM.