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Article Dans Une Revue Neural Networks Année : 1999

Application of neural networks to the modelling of some constitutive laws

Résumé

This study investigates the modelling of constitutive laws of materials by neural networks. Material behaviour is no longer represented mathematically but is described by neuronal modelling. The main aim is to build a neural network directly from experimental results (the learning phase). We give several examples of constitutive laws (Hooke, Sargin, etc.) using a backpropagation algorithm. Then we show that abilities of adjustment, memorisation and anticipation of neural networks permit us to develop a method of classification of constitutive laws.

Dates et versions

hal-00815274 , version 1 (18-04-2013)

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Stéphane Pernot, Claude-Henri Lamarque. Application of neural networks to the modelling of some constitutive laws. Neural Networks, 1999, 12 (2), pp.371-392. ⟨10.1016/S0893-6080(98)00115-4⟩. ⟨hal-00815274⟩

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