PSC Ship-Selecting Model Based on Improved Particle Swarm Optimization and BP Neural Network Algorithm

2014 ◽  
pp. 425-435
Author(s):  
Tingting Yang ◽  
Zhonghua Sun ◽  
Shouna Wang ◽  
Chengming Yang ◽  
Bin Lin
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Bp Neural Network ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Model Based ◽  
Network Algorithm ◽  
Neural Network Algorithm

Image Recognition Based on Chaotic-Particle Swarm-Optimization-Neural Network Algorithm

2013 ◽  
Vol 655-657 ◽  
pp. 969-973
Author(s):  
Bo Li ◽  
Song Xin Shi ◽  
Shi Wang
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Image Recognition ◽  
Bp Neural Network ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Swarm Optimization ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Chaotic Particle Swarm Optimization

A novel image recognition method based on chaotic-particle swarm-optimization-neural network algorithm was presented. The chaotic mapping mechanism and particle swarm algorithm were used to optimize the weight and threshold of BP neural network which was applied to the recognition of image. The simulation results show this new method can overcome the problems that BP neural network is easy to fall into local optimum and sensitive to the initial value, and has better recognition rate and stronger robustness.

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