Title :
The ant system-genetic algorithm particle filter
Author :
Juan, Zhao ; Li, Dong-feng
Author_Institution :
College of Mathematics and Information Sciences, North China University of Water Resources and Electric Power, Zhengzhou, China
Abstract :
Particle filter is a statistic filtering method based on sequential simulation. It has an outstanding contribution to the nonlinear non-Gaussian dynamic system. But how to choose particle probability distributing function and deal with particle degeneration is the key to the algorithm. A new evolutional algorithm called ant system is used during the iterative recurrence of sequential important sampling. Furthermore, the particle diversity was great increased by the using of genetic across, aberrance and selection. Simulation results show that this evolutional is better than traditional particle filter in the average absolute error and variance within a short time.
Keywords :
Algorithm design and analysis; Approximation algorithms; Heuristic algorithms; Markov processes; Particle filters; Prediction algorithms; Probability distribution; Ant System; Genetic Algorithm; Particle Degeneration; Particle Filter;
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
DOI :
10.1109/ICISE.2010.5690150