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 :
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