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Applications in Noisy and Dynamic Environments

Applications in Noisy and Dynamic Environments

E. Parsopoulos Konstantinos, N. Vrahatis Michael
Copyright: © 2010 |Pages: 23
ISBN13: 9781615206667|ISBN10: 1615206663|EISBN13: 9781615206674
DOI: 10.4018/978-1-61520-666-7.ch010
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MLA

Konstantinos E. Parsopoulos and Michael N. Vrahatis. "Applications in Noisy and Dynamic Environments." Particle Swarm Optimization and Intelligence: Advances and Applications, IGI Global, 2010, pp.222-244. https://doi.org/10.4018/978-1-61520-666-7.ch010

APA

K. Parsopoulos & M. Vrahatis (2010). Applications in Noisy and Dynamic Environments. IGI Global. https://doi.org/10.4018/978-1-61520-666-7.ch010

Chicago

Konstantinos E. Parsopoulos and Michael N. Vrahatis. "Applications in Noisy and Dynamic Environments." In Particle Swarm Optimization and Intelligence: Advances and Applications. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-666-7.ch010

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Abstract

This chapter discusses the workings of PSO in two research fields with special importance in real-world applications, namely noisy and dynamic environments. Noise simulation schemes are presented and experimental results on benchmark problems are reported. In addition, we present the application of PSO on a simulated real world problem, namely the particle identification by light scattering. Moreover, a hybrid scheme that incorporates PSO in particle filtering methods to estimate system states online is analyzed, and representative experimental results are reported. Finally, the combination of noisy and continuously changing environments is shortly discussed, providing illustrative graphical representations of performance for different PSO variants. The text focuses on providing the basic concepts and problem formulations, and suggesting experimental settings reported in literature, rather than on the bibliographical presentation of the (prohibitively extensive) literature.

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