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

被引：26

作者：

Dobrzanski, LA ^{[1
]}

Kowalski, M ^{[1
]}

Madejski, J ^{[1
]}

机构：

[1] Silesian Tech Univ, Inst Engn Mat & Biomat, PL-44100 Gliwice, Poland

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 2005年 / 164卷

关键词：

ultimate tensile strength; yield point; artificial neural networks; genetic algorithms; artificial intelligence;

D O I：

10.1016/j.jmatprotec.2005.02.194

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：1500 / 1509

页数：10