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Published in:
2020 | OriginalPaper | Chapter
Thermal Suitability Scheme: Habitability Classification of Exoplanets
Author : Suryoday Basak
Published in: Modeling, Machine Learning and Astronomy
Publisher: Springer Singapore
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Abstract
In this paper, a metric for estimating the potential habitability of exoplanets, called thermal suitability score (TSS) is developed based on machine learning (ML). As compared to prior literature, the TSS ascertains habitability by using a sign – positive for potentially habitable, and negative for non-habitable – and a number indicating the extent to which an exoplanet is habitable or non-habitable. The TSS is used on the data provided in the University of Puerto Rico’s Planetary Habitability Laboratory’s Exoplanets Catalog (PHL-EC).