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Open AccessArticle

A Comparative Study on Evolutionary Multi-objective Optimization Algorithms Estimating Surface Duct

College of Meteorology and Oceanology, National University of Defense Technology, Nanjing 211101, China
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Sensors 2018, 18(12), 4428; https://doi.org/10.3390/s18124428
Received: 10 December 2018 / Revised: 12 December 2018 / Accepted: 12 December 2018 / Published: 14 December 2018
(This article belongs to the Special Issue Computational Intelligence in Remote Sensing)
The problem of atmospheric duct inversion is usually solved as a single objective optimization problem. Based on ground-based Global Positioning System (GPS) phase delay and propagation loss, this paper develops a multi-objective method including the effect of source frequency and receiving antenna height. The diversity and convergence of solution sets are evaluated for seven multi-objective evolutionary algorithms with three performance metrics: Hypervolume (HV), Inverted Generational Distance (IGD), and the averaged Hausdorff distance ( Δ 2 ). The inversion results are compared with the simulation results, and the experimental comparison is conducted on three groups of test situations. The results demonstrate that the ranking of algorithm performance varies because of the different methods used to calculate performance metrics. Moreover, when the algorithms show overwhelming performance using performance metrics, the inversion result is not more close to the real value. In the comparison of computational experiments, it was found that, as the retrieved parameter dimension increases, the inversion result becomes more unstable. When the observed data are sufficient, the inversion result seems to be improved. View Full-Text
Keywords: multi-objective optimization algorithm; atmospheric duct; GPS, hypervolume; inverted generational distance multi-objective optimization algorithm; atmospheric duct; GPS, hypervolume; inverted generational distance
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Liao, Q.; Sheng, Z.; Shi, H.; Zhang, L.; Zhou, L.; Ge, W.; Long, Z. A Comparative Study on Evolutionary Multi-objective Optimization Algorithms Estimating Surface Duct. Sensors 2018, 18, 4428.

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