Digital image processing with dynamical neural networks for resource management: simulation experiments

In this paper, we presented some results of the extended simulations of the images of the real-world applying to the maximum entropy variational analysis algorithm with computational implementation of the recurrent neural networks to the natural resource management. To the try the computational efficient of the new propose, we are applying two metrics to the quantitative evaluation, the improvement output signal to noise ratio and mean square error. Furthermore, we present a numerical examples of the natural resource management, specifically on the Lerma river to the illustrate the efficiency of the proposed approach. To other hand, the simulation examples, can show the efficiency qualitative of the proposed approach.