Prediction of density, porosity and hardness in aluminum-copper-based composite materials using artificial neural network

Journal of Materials Processing Technology

Volumn 209, Issue 2, 2009, Pages 894-899

  Hassan, Adel Mahamood ^a   Alrashdan, Abdalla ^a   Hayajneh, Mohammed T ^a   Mayyas, Ahmad Turki ^a  

^a JORDAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Jordan)

Author keywords

Aluminum matrix composites; Artificial neural network; Compocasting; Hardness; Metal matrix composite

Indexed keywords

ALLOYING ELEMENTS; ALUMINA; ALUMINUM; BACKPROPAGATION; CARBON FIBER REINFORCED PLASTICS; COPPER; HARDNESS; LIGHT METALS; MATERIALS PROPERTIES; METALLIC MATRIX COMPOSITES; METROPOLITAN AREA NETWORKS; REINFORCEMENT; SILICON CARBIDE; VEGETATION;

ALUMINUM MATRIX COMPOSITES; ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION NEURAL NETWORKS; CARBIDE COMPOSITES; COMPOCASTING; INPUT VECTORS; METAL MATRIX COMPOSITE; METAL MATRIXES; PREDICTED VALUES; REINFORCED PARTICLES; REINFORCEMENT PARTICLES; RELATIVE ERRORS; TESTING TIMES; WEIGHT PERCENTAGES;

NEURAL NETWORKS;

EID: 58149145882     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2008.02.066     Document Type: Article

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