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Comparaison de l'ANN et du RSM dans la prédiction de la résistance du béton

Comparaison de l'ANN et du RSM dans la prédiction de la résistance du béton


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About the Book

Cette étude présente une étude comparative entre le réseau neuronal artificiel (ANN) et la méthodologie de surface de réponse (RSM) pour prédire la résistance à la compression du béton à haute résistance. La comparaison a été effectuée sur la base des mêmes ensembles de données expérimentales. Les données d'entrée examinées dans cette étude étaient le pourcentage de ciment, de fumée de silice et d'agrégats grossiers. Les méthodes employées dans l'ANN et le RSM étaient respectivement le réseau neuronal feedforward et le composite central centré sur la face. La comparaison entre les deux modèles a montré que le RSM était plus performant que l'ANN avec un coefficient de détermination (R2) plus proche de 1 avec 0,9959. En outre, tous les résultats prédits par le modèle RSM par rapport aux résultats expérimentaux se situent dans une marge de 10 %. En revanche, trois des résultats prédits par le modèle ANN se situaient en dehors de la marge de 10 %. La fumée de silice s'est également avérée avoir un impact plus important sur la résistance à la compression du béton que les granulats grossiers.


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Product Details
  • ISBN-13: 9786205997451
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Editions Notre Savoir
  • Height: 229 mm
  • No of Pages: 60
  • Spine Width: 4 mm
  • Width: 152 mm
  • ISBN-10: 6205997452
  • Publisher Date: 09 Jun 2023
  • Binding: Paperback
  • Language: French
  • Returnable: N
  • Weight: 154 gr


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