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In this paper, we show how the quasinormal modes (QNMs) arise from theperturbations of massive scalar fields propagating in the curved background byusing the artificial neural networks. To this end, we architect a specialalgorithm for the feedforward neural network method (FNNM) to compute the QNMscomplying with the certain types of boundary conditions. To test thereliability of the method, we consider two black hole spacetimes whose QNMs arewell-known: $4D$ pure de Sitter (dS) and five-dimensional Schwarzschild anti-deSitter (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 withtheir former QNM results resulting from the other methods. Therefore, ourmethod of finding the QNMs can be used for other curved spacetimes that obeythe same boundary conditions.

Quasinormal modes of dS and AdS Black Holes: Feedforward neural network method