Training strategies of Multilayer Perceptron network for study in three-phase flow

Autores

  • César Marques Salgado DIRA/IEN
  • Roos Sophia de Freitas Dam PEN/COPPE/UFRJ
  • William Luna Salgado PEN/COPPE/UFRJ

Resumo

This report presents a methodology based on nuclear techniques combined with artificial neural network (ANN) that have been used in order to predict fluid volume fractions (FVFs) using data obtained from gamma-ray radiation detectors. This research proposes investigations and comparisons of training strategies based on dual-modality principles using two NaI(Tl) detectors.

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Publicado

2021-08-12

Como Citar

Marques Salgado, C., Dam, R. S. de F., & Luna Salgado, W. (2021). Training strategies of Multilayer Perceptron network for study in three-phase flow. Instituto De Engenharia Nuclear: Progress Report, (4). Recuperado de https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/431

Edição

Seção

Application of Nuclear Techniques in Industry