Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model
Abstract
This paper is analyzing Uranium clusters mathematically as well through artificial intelligence discrete fractional order model of four different phases. The model is classifying the decay into the N i for i = 1 , 2 , 3 , 4 with different convergence rates λ i for i = 1 , 2 , 3 , 4 and α ⊛ and β . The model is first analysed for the mathematical validation including existence criteria and stability results. After these, a mathematical scheme based on the discretization is constructed and is applied to an initial data. The model is solved for the novel solutions and simulations for the fractional order 0.98 with variant parametric values. These results numerical results are then tested and affirmed with best validation performance by the use of artificial intelligence. We have observed a tremendous results of R = 1 with normal distribution of the clusrting data around the zero error.