Neural networks analysis of steel plate processing augmented by multi-objective genetic algorithms

F. Pettersson*, N. Chakraborti, S. B. Singh

*Korresponderande författare för detta arbete

Forskningsoutput: TidskriftsbidragArtikelVetenskapligPeer review

22 Citeringar (Scopus)

Sammanfattning

An earlier neural network analysis of processing of steel plates through hot rolling was subjected to a further refined analysis through some flexible neural networks that evolved using a multi-objective predator-prey genetic algorithm. The original data set expressing the Yield Strength and Ultimate Tensile Strength of the rolled slabs in terms of a total of 108 process variables were subjected to a systematic pruning through this evolutionary approach, till the nitrogen content of the steel emerged as the most significant input variable. A theoretical explanation is provided for this slightly unexpected result.

OriginalspråkEngelska
Sidor (från-till)890-898
Antal sidor9
TidskriftSteel Research International
Volym78
Utgåva12
DOI
StatusPublicerad - dec 2007
MoE-publikationstypA1 Tidskriftsartikel-refererad

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