2009
DOI: 10.1016/j.powtec.2009.05.025
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Comparison between two types of Artificial Neural Networks used for validation of pharmaceutical processes

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Cited by 44 publications
(20 citation statements)
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“…As the network architecture of the GR is determined by the size of the dataset and the number of causal factors, it is precise and robust. A previous study also found that prediction accuracy was greater with GR than with MLP 18. The LIN model only had high predictive ability for TS B .…”
mentioning
confidence: 74%
“…As the network architecture of the GR is determined by the size of the dataset and the number of causal factors, it is precise and robust. A previous study also found that prediction accuracy was greater with GR than with MLP 18. The LIN model only had high predictive ability for TS B .…”
mentioning
confidence: 74%
“…ANN can process a large amount of data simultaneously, establishing the relationship between the input and output of the system through learning. This systematic model has been widely employed in various areas for calculations and predictions [19]. ANN is supervised learning network featuring high accuracy, high learning speed, and capacities to use continuous values as input, handle complex sample identification, and process nonlinear function compositions.…”
Section: Theorymentioning
confidence: 99%
“…Learning of the considered Multilayer Perceptron, is done using the backpropagation algorithm, the modification of network weights is done by the Levenberg-Marquardt method, it is designated in MATLAB ® by TRAINLM [20,21].…”
Section: Fig 5 Building the Neural Networkmentioning
confidence: 99%