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. © 2013 Springer-Verlag.
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Chen, T. J., Wu, L. L., Liang, J. J., & Zhou, Q. H. (2013). Research and analysis on ionospheric composition based on particle swarm optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7996 LNAI, pp. 596–604). https://doi.org/10.1007/978-3-642-39482-9_69
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