DocumentCode
456785
Title
The Dynamic Grey Radial Basis Function Prediction Model and its Applications
Author
Jingling Yuan ; Luo Zhong ; Yang Yu
Author_Institution
Comput. Sch., Wuhan Univ. of Technol.
Volume
2
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
582
Lastpage
586
Abstract
The dynamic gray radial basis function (DGRBF) prediction model is the improvement of traditional dynamic grey prediction model GM (1,1). It gives the dynamic algorithm of acquiring optimized initial conditions and identifying parameters like metabolism, and then the model combines the characters of RBF neural networks, and therefore has the ability of dynamic prediction on small volume of samples. The DGRBF prediction model has been applied in the practical engineering successfully, and the experiment results demonstrate that model and its intelligent optimizing algorithm are capable of predicting in a long term and the desired data could be acquired accurately, easily and conveniently
Keywords
grey systems; radial basis function networks; structural engineering computing; RBF neural network; Shenzhen Civil Center; dynamic grey radial basis function prediction model; intelligent health monitoring system; intelligent optimizing algorithm; large-scale roof lattice structure; Application software; Biochemistry; Data engineering; Differential equations; Fuzzy neural networks; Heuristic algorithms; Mathematical model; Neural networks; Predictive models; Probability;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.360
Filename
1692054
Link To Document