论文标题
用于在天体调查中检测双星的自适应算法
An adaptive algorithm for detecting double stars in astrometric surveys
论文作者
论文摘要
该论文开发了一种基于使用机器学习（ML）方法的天体目录的方法来检测光学二进制恒星的方法。通过应用建议的方法，以河马任务目录和Pan-Starrs（PS1）目录进行了计算实验。它表明，预测出色的二元性的可靠性达到90-95％。我们注意到创建专有研究平台-Cognotron的前景和有效性。
The paper develops a method for detecting optical binary stars based on the use of astrometric catalogs in combination with machine learning (ML) methods. A computational experiment was carried out on the example of the HIPPARCOS mission catalog and the Pan-STARRS (PS1) catalog by applying the suggested method. It has shown that the reliability of predicting a stellar binarity reaches 90-95%. We note the prospects and effectiveness of creating a proprietary research platform - Cognotron.
