Title of article :
Methodology of the mechanical properties prediction for the metallurgical products from the engineering steels using the Artificial Intelligence methods
Author/Authors :
L.A. Dobrzanski، نويسنده , , M. Kowalski، نويسنده , , J. Madejski، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
10
From page :
1500
To page :
1509
Abstract :
The paper presents the new method for forecasting the yield point and the ultimate tensile strength for steel. These parameters are calculated basing on the chemical composition and technological factors of steel manufacturing. The artificial neural network technology was used for development of models making prediction of these properties possible. Software was developed, basing on these models, searching for the optimum chemical composition of steel, so that – at the particular conditions of the technological process – the risk of manufacturing the products that would not meet the requirements of the pertinent standards would be minimised. Search for the optimum chemical composition makes use of the genetic algorithms.
Keywords :
Artificial intelligence , Genetic algorithms , Yield point , Artificial neural networks , Ultimate tensile strength
Journal title :
Journal of Materials Processing Technology
Serial Year :
2005
Journal title :
Journal of Materials Processing Technology
Record number :
1179483
Link To Document :
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