Title :
An improved particle swarm optimizer with momentum
Author :
Xiang, Tao ; Wang, Jun ; Liao, Xiaofeng
Author_Institution :
Chongqing Univ., Chongqing
Abstract :
In this paper, an improved particle swarm optimization algorithm with momentum (mPSO) is proposed based on inspiration from the back propagation (BP) learning algorithm with momentum in neural networks. The momentum acts as a lowpass filter to relieve excessive oscillation and also extends the PSO velocity updating equation to a second-order difference equation. Experimental results are shown to verify its superiority both in robustness and efficiency.
Keywords :
backpropagation; difference equations; neural nets; particle swarm optimisation; back propagation learning algorithm; lowpass filter; momentum; neural networks; particle swarm optimization; second-order difference equation; Acceleration; Birds; Cultural differences; Difference equations; Educational institutions; Filters; Marine animals; Neural networks; Particle swarm optimization; Robustness;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4424903
