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The isothermal gas sphere is a particular type of Lane-Emden equation and isused widely to model many problems in astrophysics like stars, star clusters,and the formation of galaxies. In this paper, we present a computational schemeto simulate the conformable fractional isothermal gas sphere using anartificial neural network (ANN) technique and compare the obtained results withthe analytical solution deduced using the Taylor series. We performed ourcalculations, trained the ANN, and tested it using a wide range of thefractional parameter. Besides the Emden functions, we calculated themass-radius relations and the density profiles of the fractional isothermal gasspheres. The results obtained provided that ANN could perfectly simulate theconformable fractional isothermal gas spheres.

Artificial Neural Network Modeling of the Conformable Fractional Isothermal Gas Spheres