Application of Artificial Neural Networks for the Alloy Features Assessment Based on the Alloy Compound

被引：0

作者：

Sydikhov, A. S. ^{[1
]}

Tyagunov, A. G. ^{[1
]}

Milder, O. B. ^{[1
]}

Ganeev, A. A. ^{[2
]}

机构：

[1] Ural Fed Univ, Mira Str 19, Ekaterinburg 620002, Russia

[2] Ufa State Aviat Tech Univ, Marxastr 12, Ufa 450008, Russia

来源：

INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM-2018) | 2019年 / 2116卷

关键词：

Nickel-based superalloys; Artificial neural networks; Relative root mean squared error;

D O I：

10.1063/1.5114195

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Nickel-based superalloys are compositions with complex doping. A large amount of data on the chemical composition and heat resistance of nickel alloys has been accumulated, however, there is also a lot of information on the properties that is absent and this is a problem. Modern information technologies have allowed substantiating a new approach to the analysis of service characteristics of metallic materials using artificial neural networks. The previously obtained real test data served as the basis for evaluating the missing values. Transformation of input data significantly increases the accuracy of calculations. As a result, a database for 210 marks of nickel-based superalloys and their heat resistance under different conditions was obtained.

引用

页数：4

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