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Neural network programming in bioprocess variable estimation and state prediction

Linko, Pekka ; Zhu, Yihong

Journal of biotechnology, 1991-12, Vol.21 (3), p.253-269 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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Título:
Neural network programming in bioprocess variable estimation and state prediction
Autor: Linko, Pekka ; Zhu, Yihong
Assuntos: Algorithms ; back propagation ; biochemistry ; Biological and medical sciences ; Biotechnology ; Biotechnology - methods ; computer applications ; Computer Simulation ; Fundamental and applied biological sciences. Psychology ; General aspects ; Kinetics ; machine learning ; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) ; Neural network ; neural networks ; Neural Networks (Computer) ; process engineering ; State prediction ; Variable estimation
É parte de: Journal of biotechnology, 1991-12, Vol.21 (3), p.253-269
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
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Descrição: A neural network program with efficient learning ability for bioprocess variable estimation and state prediction was developed. A 3 layer, feed-forward neural network architecture was used, and the program was written in Quick C ver 2.5 for an IBM compatible computer with a 80486/33 MHz processor. A back propagation training algorithm was used based on learning by pattern and momentum in a combination as used to adjust the connection of weights of the neurons in adjacent layers. The delta rule was applied in a gradient descent search technique to minimize a cost function equal to the mean sqaure difference between the target and the network output. A non-linear, sigmoidal logistic transfer function was used in squashing the weighted sum of the inputs of each neuron to a limited range output. A good neural network prediction model was obtained by training with a sequence of past time course data of a typical bioprocess. The well trained neural network estimated accurately and rapidly the state variables with or without noise even under varying process dynamics.
Editor: Lausanne: Elsevier B.V
Idioma: Inglês

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Neural network programming in bioprocess variable estimation and state prediction

Linko, Pekka ; Zhu, Yihong

Lausanne: Elsevier B.V

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