ARTIFICIAL NEURAL NETWORK MODELING OF THE CONFORMABLE FRACTIONAL ISOTHERMAL GAS SPHERES

The isothermal gas sphere is a particular type of Lane-Emden equation and used widely to model many problems in astrophysics, like the formation stars, star clusters galaxies. In this paper, we present computational scheme simulate conformable fractional using an artificial neural network (ANN) technique, compare obtained results with analytical solution deduced Taylor series. We performed our calculations, trained ANN, tested it wide range parameter. Besides Emden functions, calculated mass-radius relations density profiles spheres. show that ANN could perfectly