Neural network frames. Application to biochemical kinetic diagnosis
Identifieur interne : 002F87 ( Main/Merge ); précédent : 002F86; suivant : 002F88Neural network frames. Application to biochemical kinetic diagnosis
Auteurs : O. Iordache [France] ; J. P. Corriou ; L. Garrido-Sanchez ; C. Fonteix ; Daniel Tondeur [France]Source :
- Computers & chemical engineering [ 0098-1354 ] ; 1993.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
The diagnosis of chemical kinetics in chemical plants can be viewed as a process of classification. Recorded data can be associated with different types of kinetic models and the type of kinetics can be classified by comparison with previously recorded data. A new frame for a neural network (NN) is proposed in order to carry out the classification. The potentialities of this adaptive, hierarchized frame organized as a «polystochastic» model have been investigated here. The underlying approach is based on the use of distances between two paths of observed kinetic data. A matrix of distances results from a set of possible kinetic models, and algorithms for classifying models are developed using this matrix
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Pascal:94-0034164Le document en format XML
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<front><div type="abstract" xml:lang="en">The diagnosis of chemical kinetics in chemical plants can be viewed as a process of classification. Recorded data can be associated with different types of kinetic models and the type of kinetics can be classified by comparison with previously recorded data. A new frame for a neural network (NN) is proposed in order to carry out the classification. The potentialities of this adaptive, hierarchized frame organized as a «polystochastic» model have been investigated here. The underlying approach is based on the use of distances between two paths of observed kinetic data. A matrix of distances results from a set of possible kinetic models, and algorithms for classifying models are developed using this matrix</div>
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