ANN model for prediction of the effects of composition and process parameters on tensile strength and percent elongation of Si - Mn TRIP steels

Materials Science and Engineering: A

Volumn 374, Issue 1-2, 2004, Pages 122-128

  Hosseini, S M K ^a   Zarei Hanzaki, A ^a   Yazdan Panah, M J ^a   Yue, S ^b  

^a UNIVERSITY OF TEHRAN   (Iran)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Artificial neural network; Back propagation algorithm; Intercritical annealing; Modeling; Si Mn TRIP steel; Supervised learning

Indexed keywords

ALGORITHMS; ANNEALING; BACKPROPAGATION; MATHEMATICAL MODELS; MICROSTRUCTURE; NEURAL NETWORKS; SILICON COMPOUNDS; TENSILE STRENGTH; TOPOLOGY;

BAINITIC HOLDING TREATMENT; PERCENTAGE ELONGATION; PROCESS PARAMETERS;

STEEL;

HEAT TREATMENT;

EID: 2642519638     PISSN: 09215093     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.msea.2004.01.007     Document Type: Article

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