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Using probabilistic neural network to analyze the binary starsSchulte 3, EY Cep, HD 101131, and Haro 1-14c |
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| รหัสดีโอไอ | |
| Creator | 1. Ali Pirkhedri 2. Kamal Ghaderi |
| Title | Using probabilistic neural network to analyze the binary starsSchulte 3, EY Cep, HD 101131, and Haro 1-14c |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2561 |
| Journal Title | Songklanakarin Journal of Science and Technology |
| Journal Vol. | 40 |
| Journal No. | 3 |
| Page no. | 676 |
| Keyword | probabilistic neural network, binary systems, eclipsing, velocity curve |
| URL Website | http://rdo.psu.ac.th/sjstweb/index.php |
| ISSN | 0125-3395 |
| Abstract | The use of artificial neural networks (ANNs) in physical sciences has increased recently. Determining the orbitalelements of binary systems helps us to obtain fundamental information. In this paper, ANNs were used to find the correspondingorbital and spectroscopic elements of four double-lined spectroscopic binary stars: Schulte 3, EY Cep, HD 101131, and Haro 1-14c. The orbital parameters of the radial velocity curve obtained from ANNs were compared with other traditional methods andwe show that the proposed method is of high accuracy. Our numerical results are in good agreement with those obtained byothers using nonlinear regression methods. We show the validity of our new method in a wide range of different types of binary.In this method, the time consumed is considerably less than in the other traditional methods. The present method is applicable toorbits of all eccentricities and inclination angles and enables one to vary all of the unknown parameters simultaneously. |
