22 citations · 39 across the 9 of their papers we have counts for
9 papers
Detection of Quadruple Structure Near the ASCC 32 Region via Machine Learning Methods
Mohammad Noormohammadi, Atefeh Javadi, Mehdi Khakian Ghomi
Multiple structures within stellar groups are an intriguing subject for theoretical and observational studies of stellar formation. With the accuracy and completeness of data from…
Detection of Open Cluster Members Inside and Beyond Tidal Radius by Machine Learning Methods Based on Gaia DR3
Mohammad Noormohammadi, Mehdi Khakian Ghomi, Atefeh Javadi
In our previous work, we introduced a method that combines two unsupervised algorithms: DBSCAN and GMM. We applied this method to 12 open clusters based on Gaia EDR3 data, demonstr…
The membership of stars, density profile and mass segregation in open clusters using a new machine learning-based method
Mohammad Noormohammadi, Mehdi Khakian Ghomi, Hossein Haghi
A combination of two unsupervised machine learning algorithms, DBSCAN and GMM are used to find members with a high probability of twelve open clusters, M38, NGC2099, Coma Ber, NGC7…
A New Simple Method for the Analysis of Extensive Air Showers
H. Hedayati Kh., A. Anvari, M. Bahmanabadi +2
The most important goal of studying an extensive air shower is to find the energy, mass and arrival direction of its primary cosmic ray. In order to find these parameters, the core…
New Simple Method for Analysis of Extensive Air Showers
H. Hedayati Kh., A. Anvari, M. Bahmanabadi +2
Cosmic rays have valuable information about universe surroundings us. Finding energy, mass and arrival direction of primary cosmic ray particle are the most important aspects of ex…
On Shadow of the Moon in Extensive Air Shower Data
F. Sheidaei, M. Bahmanabadi, M. Khakian Ghomi +3
A new technique has been devised for the analysis of extensive air shower data in observing the effect of the moon on this data. In this technique the number of EAS events with arr…