Localizing Multiple odor Sources in a dynamic environment based on Modified niche Particle Swarm Optimization with flow of wind

Wisnu Jatmiko; A. Nugraha; R. Effendi; W. Pambuko; R. Mardian; K. Sekiyama; T. Fukuda

Localizing Multiple odor Sources in a dynamic environment based on Modified niche Particle Swarm Optimization with flow of wind

Wisnu Jatmiko, A. Nugraha, R. Effendi, W. Pambuko, R. Mardian, K. Sekiyama, T. Fukuda

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

29 Citations (Scopus)

Abstract

A new algorithm based on Modified Particle Swarm Optimization (MPSO) that follows is a local gradient of a chemical concentration within a plume and follows the direction of the wind velocity is investigated. Moreover, the niche characteristic is adopted to solve the multi-peak and multi-source problem. Simulations results demonstrate that the new approach is reliable for The Advection-Diffusion odor robotic model. Finally, the statistical analysis shows this new approach is technically sound.

Original language	English
Pages (from-to)	1187-1196
Number of pages	10
Journal	WSEAS Transactions on Systems
Volume	8
Issue number	11
Publication status	Published - Nov 2009

Keywords

Modified niche PSO
Multiple odor sources localization

Cite this

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abstract = "A new algorithm based on Modified Particle Swarm Optimization (MPSO) that follows is a local gradient of a chemical concentration within a plume and follows the direction of the wind velocity is investigated. Moreover, the niche characteristic is adopted to solve the multi-peak and multi-source problem. Simulations results demonstrate that the new approach is reliable for The Advection-Diffusion odor robotic model. Finally, the statistical analysis shows this new approach is technically sound.",

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AU - Jatmiko, Wisnu

AU - Nugraha, A.

AU - Effendi, R.

AU - Pambuko, W.

AU - Mardian, R.

AU - Sekiyama, K.

AU - Fukuda, T.

PY - 2009/11

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AB - A new algorithm based on Modified Particle Swarm Optimization (MPSO) that follows is a local gradient of a chemical concentration within a plume and follows the direction of the wind velocity is investigated. Moreover, the niche characteristic is adopted to solve the multi-peak and multi-source problem. Simulations results demonstrate that the new approach is reliable for The Advection-Diffusion odor robotic model. Finally, the statistical analysis shows this new approach is technically sound.

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KW - Multiple odor sources localization

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Localizing Multiple odor Sources in a dynamic environment based on Modified niche Particle Swarm Optimization with flow of wind

Abstract

Keywords

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