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Andreas M. Chwatal and Günther R. Raidl apply metaheuristics, specifically evolution strategies and scatter search, to fit rectangular signals to time-series data, with the goal of detecting exoplanet-transit signals in stellar photometric observation data. The problem is formulated as a continuous parameter optimization problem, where the objective is to minimize the deviation between the model and observations. The authors perform a fitness-landscape analysis, which confirms the difficulty of the problem due to strong mutual dependencies of the parameters. They then propose and evaluate the performance of evolution strategies and scatter search algorithms, optionally combined with local optimization methods, on artificial test instances with varying numbers of signals and noise levels.

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Andreas M. Chwatal and Günther R.

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  • File Format: PDF
  • File Size: 107 KB
  • Pages: 4
  • Language: EN
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