Implementation of Recurrent Artificial Neural Networks for Nonlinear Dynamic Modeling in Biomedical Applications

2013 ◽  
Vol 36 (11) ◽  
pp. 833-842
Author(s):  
Miona V. Andrejević Stošović ◽  
Vančo B. Litovski
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dynamic Modeling ◽  
Nonlinear Dynamic ◽  
Biomedical Applications ◽  
Artificial Neural ◽  
Recurrent Artificial Neural Networks ◽  
Nonlinear Dynamic Modeling

scholarly journals Dynamic Modeling of Streptomyces hygroscopicus Fermentation Broth Microfiltration by Artificial Neural Networks

2019 ◽  
Author(s):  
Aleksandar Jokić ◽  
Nevenka Nikolić ◽  
Nataša Lukić ◽  
Jovana Grahovac ◽  
Jelena Dodić ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dynamic Modeling ◽  
Fermentation Broth ◽  
Optimal Number ◽  
Streptomyces Hygroscopicus ◽  
Transmembrane Pressure ◽  
Ann Model ◽  
Permeate Flux ◽  
Artificial Neural

Artificial neural networks (ANNs) have been used to dynamically model cross-flow microfiltration of Streptomyces hygroscopicus fermentation broths. The aim is to predict permeate flux as a function of temperature, feed flow, transmembrane pressure and processing time. Dynamic modeling of microfiltration performance of complex systems (such as broths) is very important for design of new processes and better understanding of the present. The results of ANN model analysis suggest that the coefficients of the determination have high values. The application of the Bayesian regularization gave better results to the performance of the neural network compared to the Levenberg-Marquet algorithm. The optimal number of neurons in the hidden layer is eight. Analysis of the absolute relative error showed excellent permeate flux estimates for 100 % of the data points, with an error less than 5 % for the data obtained during microfiltration in the presence of a turbulence promoter. Whilst in the case of microfiltration without turbulence promoter 90 % of predictions have an error less than 10 %. The results of applying the concept of neural networks in the dynamic modeling of microfiltration of Streptomyces hygroscopicus fermentative broths with and without a turbulence promoter clearly show the validity of proposed method for simulation and prediction of microfiltration experimental results.

Artificial neural networks for predicting nonlinear dynamic helicopter loads

AIAA Journal ◽  
1994 ◽  
Vol 32 (5) ◽  
pp. 1072-1077 ◽  
Author(s):  
A. B. Cook ◽  
C. R. Fuller ◽  
W. F. O'Brien ◽  
R. H. Cabell
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Nonlinear Dynamic ◽  
Artificial Neural

scholarly journals Weekly forecast of the Settlement Price of Differences in the Brazilian short-term market through recurrent artificial neural networks

2019 ◽  
Author(s):  
Fabiane Barbosa do Nascimento ◽  
Leonardo Rocha Olivi ◽  
Luís Henrique Lopes Lima ◽  
Leonardo Willer de Oliveira ◽  
Ivo Chaves Silva Junior
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Short Term ◽  
Artificial Neural ◽  
Recurrent Artificial Neural Networks
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