DocumentCode :
518370
Title :
Improvement of Hopfield neural network algorithm
Author :
Gao, Yanping ; Deng, Changhui ; Jiang, Guoxing
Author_Institution :
Sch. of Inf. Eng., Dalian Fisheries Univ., Dalian, China
Volume :
6
fYear :
2010
fDate :
16-18 April 2010
Abstract :
This paper presents an improved algorithm based on Hopfield neural network, describes how to achieve TSP problem solution. And after the analysis of the method deficiencies, it respectively improves the existing algorithm in parameter setting and energy functions, and proposes further improvements for the algorithm according to the phenomenon of repeat solutions. Finally, it gives the results of the improved algorithm. The experimental results show that the improved algorithm can greatly improve the solving speed and convergence rate.
Keywords :
Hopfield neural nets; travelling salesman problems; Hopfield neural network algorithm; TSP problem solution; energy functions; Algorithm design and analysis; Aquaculture; Artificial intelligence; Artificial neural networks; Cities and towns; Hopfield neural networks; Lyapunov method; Neurons; Power engineering and energy; Stability analysis; TSP problem; energy function; improved algorithm; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
Type :
conf
DOI :
10.1109/ICCET.2010.5486096
Filename :
5486096
Link To Document :
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