Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
380636 | Engineering Applications of Artificial Intelligence | 2014 | 8 Pages |
Abstract
Based on Ant Colony Optimization for Continuous Domains (ACORACOR) and Particle Filter (PF), an intelligent particle filter, namely Ant Colony Estimator (ACE), is proposed in this paper. Modeling and search abilities of ACORACOR are incorporated into the standard particle filtering framework to improve the estimation performance and overcome the well-known problems of Degeneracy and Sample Impoverishment. ACORACOR operators implicitly use measurement and previous particle information, to generate probably better particles. Simulation results are given for two examples and ACE is compared to other types of particle filters. The obtained results confirm the efficiency and applicability of ACE.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
S. Mostapha Kalami Heris, Hamid Khaloozadeh,