Now showing items 1-3 of 3
Sensitivity analysis of a mechanistic growth model of Escherichia coli
A detailed mechanistic model, with a large number of metabolites and parameters, describing growth of a single cell of the bacterium Escherichia coli is simulated and the resulting predictions are compared with available ...
Application of back-propagation neural networks to the modeling and control of multiple-input, multiple-output processes
Certain properties of back-propagation neural networks have been found to be useful in structuring models for multiple-input, multiple-output (MIMO) processes. The network's simplicity and its ability to identify the ...
Application of back-propagation neural networks to system identification and process control
Certain properties of the back-propagation neural network have been found to be potentially useful in structuring models for process control applications. The network's relative simplicity and its ability to learn by example ...