Optimizing the Individual Differences of EEG Signals through BP Neural Network Algorithm for a BCI Dialing System

2013 ◽  
pp. 479-488 ◽  
Author(s):  
Dongxue Lin ◽  
Feng Duan ◽  
Wenyu Li ◽  
Jingyao Shen ◽  
Qing Mei Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Individual Differences ◽  
Bp Neural Network ◽  
Eeg Signals ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
The Individual

Precision Power System Harmonic Analysis Algorithm Based on ABC-BPNN

2013 ◽  
Vol 483 ◽  
pp. 630-634
Author(s):  
Shu Chuan Gan ◽  
Ling Tang ◽  
Li Cao ◽  
Ying Gao Yue
Keyword(s):  
Neural Network ◽  
Power System ◽  
Harmonic Analysis ◽  
Bp Neural Network ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimal Solution ◽  
Bee Colony ◽  
Network Algorithm ◽  
Neural Network Algorithm

An algorithm of artificial colony algorithm to optimize the BP neural network algorithm was presented and used to analyze the harmonics of power system. The artificial bee colony algorithm global searching ability, convergence speed for the BP neural network algorithm for harmonic analysis is easy to fall into local optimal solution of the disadvantages, and the initial weights of the artificial bee colony algorithm also greatly enhance whole algorithm model generalization capability. This algorithm using MATLAB for Artificial bee colony algorithm and BP neural network algorithm simulation training toolbox found using artificial bee colony algorithm to optimize BP neural network algorithm converges faster results with greater accuracy, with better harmonic analysis results.

Sign in / Sign up

Export Citation Format

Share Document