DocumentCode
530614
Title
The costs prediction of AOD furnace based on improved RBF neural network
Author
Na, Tang ; De-jiang, Zhang ; Hui, Li
Author_Institution
Changchun Inst. of Opt., Fine Mech. & Phys., Grad. Univ. of Chinese Acad. of Sci., Changchun, China
Volume
4
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
523
Lastpage
526
Abstract
In order to predict the cost, a model of cost prediction was set up based on adaptive hierarchical genetic algorithm and RBF neural network. Hierarchical genetic algorithm could optimize the topology and the parameters simultaneously. Compared with simple genetic algorithm, it has more efficiency in not only accelerating and stabilizing the parameters training but also determining the structure of the network. Adaptive crossover and mutation probability could accelerate the speed and avoid prematurity. The model was tested by five samples. The results showed that the prediction model has high prediction accuracy, which indicated that it was applicable to predict the cost by the model.
Keywords
costing; furnaces; genetic algorithms; radial basis function networks; topology; AOD furnace; RBF neural network; adaptive hierarchical genetic algorithm; cost prediction; radial basis function neural network; Furnaces; Genetics; Legged locomotion; Predictive models; AOD furnace; RBF neural network; adaptive hierarchical genetic algorithm; cost prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4244-7957-3
Type
conf
DOI
10.1109/CMCE.2010.5610089
Filename
5610089
Link To Document