https://doi.org/10.1140/epjp/s13360-024-05107-0
Regular Article
Artificial neural networks for the food web model
Department of Mathematics, Arba Minch University, PO BOX – 21, Arbaminch, Ethiopia
Received:
19
February
2024
Accepted:
18
March
2024
Published online:
29
April
2024
The study of this work is to present the analytical solutions of prey-predator model by using the artificial neural networks (ANN). We studied the dynamics of a food web model consisting of one prey and two predators. We discussed the positivity, boundedness and well posedness of the system. The model was expressed in the form of an input, hidden layer and output, flow chart and ANN methods. We obtained the solutions of ANN simulations by using Mathematica programming. We analyzed the physical and geometrical interpretation of the solutions. Here, we found that preypredators population exist at the beginning phase, whereas the population of prey and middle spice predator decrease with respect to time. We further found that top predator population increases due to the availability of the food.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
