Particle filtering with particle swarm optimization in systems with multiplicative noise

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Particle filtering with particle swarm optimization in systems with multiplicative noise

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents

Atlanta, GA, USA

SESSION: Ant colony optimization, swarm intelligence, and artificial immune systems papers table of contents

Pages 57-62

Year of Publication: 2008

ISBN:978-1-60558-130-9

Authors

A. D. Klamargias	University of Patras, Patras, Greece
K. E. Parsopoulos	University of Patras, Patras, Greece
Ph. D. Alevizos	University of Patras, Patras, Greece
M. N. Vrahatis	University of Patras, Patras, Greece

Sponsors

ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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ACM New York, NY, USA

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ABSTRACT

We propose a Particle Filter model that incorporates Particle Swarm Optimization for predicting systems with multiplicative noise. The proposed model employs a conventional multiobjective optimization approach to weight the likelihood and prior of the filter in order to alleviate the particle impoverishment problem. The resulting scheme is tested on a well-known test problem with multiplicative noise. Results are promising, especially in cases of high system and measurement noise levels.

REFERENCES

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