RBF-Type Artificial Neural Network Model Applied in Alloy Design of Steels

RBF model,a new type of artificial neural network model was developed to design the content of carbon in low-alloy engineering steels.The errors of the ANN model are：MSE 0.052 1,MSRE 17.85%,and VOF 1.932 9.The results obtained are satisfactory.The method is a powerful aid for designing new steels.

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Bibliographic Details
Published inJournal of iron and steel research, international Vol. 15; no. 2; pp. 87 - 90
Main Authors YOU, Wei, LIU, Ya-xiu, BAI, Bing-zhe, FANG, Hong-sheng
Format Journal Article
LanguageEnglish
Published Singapore Elsevier Ltd 01.03.2008
Springer Singapore
Department of Mechanical and Electrical Engineering, North China Institute of Science and Technology,Beijing 101601, China%Department of Electronics and Information Engineering, North China Institute of Science and Technology, Beijing 101601, China%Department of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
Subjects
alloy design
Applied and Technical Physics
artificial neural network
carbon
Engineering
Machines
Manufacturing
Materials Engineering
Materials Science
Metallic Materials
neurobalance
Physical Chemistry
Processes
radial-basis-function
人工神经网络
光线基础功能
合金设计
碳元素
artificial neural network
alloy design
radial-basis-function
neurobalance
carbon
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Summary:RBF model,a new type of artificial neural network model was developed to design the content of carbon in low-alloy engineering steels.The errors of the ANN model are：MSE 0.052 1,MSRE 17.85%,and VOF 1.932 9.The results obtained are satisfactory.The method is a powerful aid for designing new steels.
Bibliography:radial-basis-function, artificial neural network, carbon; alloy design; neurobalance
radial-basis-function, artificial neural network, carbon
alloy design
11-3678/TF
TP183
neurobalance
ISSN:1006-706X
2210-3988
DOI:10.1016/S1006-706X(08)60038-2