Modeling the correlation between heat treatment, chemical composition and bainite fraction of pipeline steels by means of artificial neural networks

被引：0

作者：

机构：

[1] Khalaj, Gholamreza

[2] 2,Pouraliakbar, Hesam

[3] 2,Mamaghani, Kaveh Rahimi

[4] Khalaj, Mohammad-Javad

来源：

| 1600年 / Institute of Computer Science Izhevsk卷 / 23期

关键词：

Pipelines - High strength alloys - Bainitic transformations - Steel pipe - Microalloying - Alloy steel - Neural networks - High strength steel;

D O I：

10.14311/nnw.2013.23.022

中图分类号：

学科分类号：

摘要：

引用

共 23 条

[1] MODELING THE CORRELATION BETWEEN HEAT TREATMENT, CHEMICAL COMPOSITION AND BAINITE FRACTION OF PIPELINE STEELS BY MEANS OF ARTIFICIAL NEURAL NETWORKS
Khalaj, Gholamreza
Pouraliakbar, Hesam
Mamaghani, Kaveh Rahimi
Khalaj, Mohammad-Javad
NEURAL NETWORK WORLD, 2013, 23 (04) : 351 - 367
[2] Retraction Note: Modeling the correlation between Charpy impact energy and chemical composition of functionally graded steels by artificial neural networks
Ali Nazari
Neural Computing and Applications, 2020, 32 : 17817 - 17817
[3] RETRACTED ARTICLE: Modeling the correlation between Charpy impact energy and chemical composition of functionally graded steels by artificial neural networks
Ali Nazari
Neural Computing and Applications, 2019, 31 : 707 - 721
[4] Modeling the Chemical Composition of Ferritic Stainless Steels with the Use of Artificial Neural Networks
Honysz, Rafal
METALS, 2021, 11 (05)
[5] Determination of volume fraction of bainite in low carbon steels using artificial neural networks
Sidhu, G.
Bhole, S. D.
Chen, D. L.
Essadiqi, E.
COMPUTATIONAL MATERIALS SCIENCE, 2011, 50 (12) : 3377 - 3384
[6] RETRACTED: Modeling the correlation between Charpy impact energy and chemical composition of functionally graded steels by artificial neural networks (Retracted Article)
Nazari, Ali
NEURAL COMPUTING & APPLICATIONS, 2019, 31 (Suppl 2): : 707 - 721
[7] Artificial Neural Networks for Hardness Prediction of HAZ with Chemical Composition and Tensile Test of X70 Pipeline Steels
Hesam POURALIAKBAR
Mohammad-javad KHALAJ
Mohsen NAZERFAKHARI
Gholamreza KHALAJ
JournalofIronandSteelResearch(International), 2015, 22 (05) : 446 - 450
[8] Artificial Neural Networks for Hardness Prediction of HAZ with Chemical Composition and Tensile Test of X70 Pipeline Steels
Pouraliakbar, Hesam
Khalaj, Mohammad-javad
Nazerfakhari, Mohsen
Khalaj, Gholamreza
JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL, 2015, 22 (05) : 446 - 450
[9] Artificial neural networks for hardness prediction of HAZ with chemical composition and tensile test of X70 pipeline steels
Hesam Pouraliakbar
Mohammad-javad Khalaj
Mohsen Nazerfakhari
Gholamreza Khalaj
Journal of Iron and Steel Research International, 2015, 22 : 446 - 450
[10] Modeling the correlation between yield strength, chemical composition and ultimate tensile strength of X70 pipeline steels by means of gene expression programming
Khalaj, Gholamreza
Khalaj, Mohammad-Javad
INTERNATIONAL JOURNAL OF MATERIALS RESEARCH, 2013, 104 (07) : 697 - 702

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