Methodology of the mechanical properties prediction for the metallurgical products from the engineering steels using the Artificial Intelligence methods

Journal of Materials Processing Technology

Volumn 164-165, Issue , 2005, Pages 1500-1509

  Dobrzanski L A ^a   Kowalski, M ^a   Madejski, J ^a  

^a SILESIAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Artificial Intelligence; Artificial neural networks; Genetic algorithms; Ultimate tensile strength; Yield point

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPOSITION; COMPUTER SOFTWARE; GENETIC ALGORITHMS; MATHEMATICAL MODELS; MECHANICAL PROPERTIES; NEURAL NETWORKS; PARAMETER ESTIMATION; STEEL METALLURGY; TENSILE STRENGTH; MANUFACTURE;

NEURAL NETWORK MODELS; TRAINING SETS; ULTIMATE TENSILE STRENGTH; YIELD POINT;

STEEL; STEEL METALLURGY;

ARTIFICIAL INTELLIGENCE METHODS; CHEMICAL COMPOSITIONS; PARTICULAR CONDITION; STEEL MANUFACTURING; TECHNOLOGICAL FACTORS; TECHNOLOGICAL PROCESS; ULTIMATE TENSILE STRENGTH; YIELD POINTS;

EID: 17844389355     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2005.02.194     Document Type: Article

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