DocumentCode
2121088
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
fYear
2010
fDate
4-6 Dec. 2010
Firstpage
1
Lastpage
4
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4244-7616-9
Type
conf
DOI
10.1109/ICISE.2010.5690150
Filename
5690150
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