Artificial Intelligence based Solver for Governing Model of Radioactivity Cooling, Self-gravitating Clouds and Clusters of Galaxies

摘要

In this study, a reliable alternate platform is developed based on artificial neural network optimized with soft computing technique for a non-linear singular system that can model complex physical phenomenas of the nature like radioactivity cooling, self-gravitating clouds and clusters of galaxies. The trial solution is mathematically represented by feed-forward neural network. A cost function is defined in an unsupervised manner that is optimized by a probabilistic meta-heuristic global search technique based on annealing in metallurgy. The results of the designed scheme are evaluated by comparing with the desired response of the system. The applicability, stability and reliability of the proposed method is validated by Monte Carlo simulations.