DocumentCode
1563325
Title
The analysis of convergence of hybrid algorithm based on Neural Network and Genetic Algorithm
Author
PAN, Mei-Qin ; HE, Guo-Ping
Author_Institution
Coll. of Inf. Sci. & Eng., Shan Dong Univ. of Sci. & Technol., Qingdao
Volume
1
fYear
2005
Firstpage
232
Lastpage
235
Abstract
This paper analyzes the advantages and disadvantages of GA and BP algorithms, and presents the iteration of hybrid algorithm based on both algorithms. The hybrid algorithm incorporates the stronger global search of GA into the stronger local search of BP, and can search out the global optimum faster than each algorithm. At last, the hybrid algorithm is proved converge to the global optimum with the probability of 1
Keywords
convergence of numerical methods; genetic algorithms; neural nets; backpropagation algorithms; convergence analysis; genetic algorithm; hybrid algorithm; neural network; Algorithm design and analysis; Biological neural networks; Convergence; Educational institutions; Genetic algorithms; Genetic mutations; Iterative algorithms; Neural networks; Paper technology; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614604
Filename
1614604
Link To Document