  In this paper, we show how the quasinormal modes (QNMs) arise from the
perturbations of massive scalar fields propagating in the curved background by
using the artificial neural networks. To this end, we architect a special
algorithm for the feedforward neural network method (FNNM) to compute the QNMs
complying with the certain types of boundary conditions. To test the
reliability of the method, we consider two black hole spacetimes whose QNMs are
well-known: $4D$ pure de Sitter (dS) and five-dimensional Schwarzschild anti-de
Sitter (AdS) black holes. Using the FNNM, the QNMs of are computed numerically.
It is shown that the obtained QNMs via the FNNM are in good agreement with
their former QNM results resulting from the other methods. Therefore, our
method of finding the QNMs can be used for other curved spacetimes that obey
the same boundary conditions.
