Application of RBF network based on artificial immune algorithm to predicting mechanical property of steel bars

Beijing Keji Daxue Xuebao/Journal of University of Science and Technology Beijing

Volumn 27, Issue 1, 2005, Pages 123-125

  Zhou, Ying ^a,b   Zheng, Deling ^a   Wang, Ying ^a   Ju, Lei ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING   (China)

^b HEBEI UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Artificial immune; Immune recognition; Mechanical property; RBF neural network; Steel bar

Indexed keywords

BARS (METAL); LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; MECHANICAL PROPERTIES; RADIAL BASIS FUNCTION NETWORKS; ROLLING; STEEL METALLURGY;

ARTIFICIAL IMMUNE ALGORITHM; IMMUNE RECOGNITION; K-MEANS ALGORITHM; STEEL BARS PROPERTY PREDICTING;

STEEL TESTING;

EID: 15744387794     PISSN: 1001053X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (6)

1. de Castro, Von Zuben. Artificial immune systems: Part I Basic theory and applications. Technical Report-RT DCA, 1999. 89
2. Hofrmann G W. A Neural network model based on the analogy with the immune system. J Theor Biol, 1986, 122: 33
3. Gomm J B, Ding L Y. Selecting radial basis function network centers with recursive orthogonal least squares training. IEEE Trans Neural Network, 2000, 11(2): 306