Numerical Solutions of Fractional Systems Using Bessel Artificial Neural Network Based Integrated Intelligent Computing

Abstract

Nowadays, fractional differential equations (FDE's), with their numerical solutions, are a developing area of research since differential equations of these sort are a frequent presence in different fields of physical sciences. In this research article, a Bessel Artificial Neural Network Technique (BANNT) has been presented to solve Systems of FDE's where fractional derivative operator (practiced here) is of a newly defined Atangana Baleanu Caputo (ABC) type. ABCFD is a modified version of caputo fractional derivative that helps in solving such systems of FDE's. This technique integrates knowledge about the FDE's into BANNT and the training sets. BANNT is being used repeatedly to solve different variety of problems addressing a wide range of disciplines. After developing the technique, the BANNT is applied to some system of differential equations of the Fractional Order. Numerous illustrations have been presented to elucidate the implementation and efficiency of the BANNT, and the numerical results obtained are then graphically plotted.