Research and analysis on ionospheric composition based on particle swarm optimization

Authors:
Tie-Jun Chen;Li-Li Wu;J. J. Liang;Qihou H. Zhou
Affiliations:
School of Electrical Engineering, Zhengzhou University, China;School of Electrical Engineering, Zhengzhou University, China;School of Electrical Engineering, Zhengzhou University, China;School of Electrical Engineering, Zhengzhou University, China,School of Engineering and Applied Science, Miami University, Oxford
Venue:
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Year:
2013

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Abstract

A new analysis method for the molecular ion composition is proposed in this paper. The ionospheric data is measured by incoherent scattering radars (ISR). Contrast to the least square method fit (LSF), which is commonly used on ionospheric composition analyses, the particle swarm optimizer (PSO) is introduced to manipulate the data from ISR. The temperature-composition (TC) dependence problem by the LSF is revisited. The parameters of the Standard Particle Swarm Optimization algorithm (SPSO) for ionospheric composition analyses are determined. Experimental results show that PSO presents a better performance comparing with LSF and can be considered as a potential solution to solve ionospheric composition analysis problem.