scholarly journals Particle Swarm Optimization with Comprehensive Learning a Self-adaptive Mutation

2015 ◽  
Author(s):  
Hao Tan ◽  
Jianjun Li ◽  
Jing Huang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Adaptive Mutation ◽  
Swarm Optimization ◽  
Self Adaptive

Power Transform Fault Diagnosis Based on the Adaptive Mutation Particle Swarm Optimization

2013 ◽  
Vol 756-759 ◽  
pp. 3804-3808
Author(s):  
Zhi Mei Duan ◽  
Jia Tang Cheng
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Power Transformer ◽  
Recognition Rate ◽  
Particle Swarm ◽  
Adaptive Mutation ◽  
Bp Network ◽  
Swarm Optimization ◽  
Fault Recognition

In order to improve the accuracy of fault diagnosis of power transformer, in this paper, a method is proposed that optimize the weight of BP neural network by adaptive mutation particle swarm optimization (AMPSO). According to the characteristic of transformer fault, the optimized neural network is used to diagnose fault of the power transformer. Individual particles action is amended by this algorithm and local minima problems of the standard PSO and BP network are overcooked. The experimental results show that, the method can classify transformer faults, and effectively improve the fault recognition rate.

Sign in / Sign up

Export Citation Format

Share Document