DocumentCode
530648
Title
Key shape recognition algorithm based on genetic neural network
Author
Yang, Hong-Tao ; Li, Hui ; Li, Xiu-Lan ; Zhao, Dan-Dan
Author_Institution
Inst. of Electr. & Electron. Eng., Changchun Univ. of Technol., Changchun, China
Volume
4
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
270
Lastpage
273
Abstract
To avoid the BP (Back-Propagation) Network´s disadvantages of low training speed, prone to trapping in a local optimum and poor capability of global search, this paper establishes the model of key based on generic algorithm with the research on the key shape, by optimizing the initialized weights and threshold of neural network with GA. After the test of the program complied by MATLAB language and the comparison with pure BP algorithm, the results show that the methods suggested by this paper improve both the accuracy of predicting and the rate of convergence.
Keywords
backpropagation; genetic algorithms; neural nets; shape recognition; BP; MATLAB language; backpropagation; generic algorithm; genetic neural network; shape recognition algorithm; Presses; Training; BP Neutral Network; Generic Algorithm; Key shape recognition;
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.2010.5610145
Filename
5610145
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