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Artificial neural networks for the food web model

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Abstract

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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Acknowledgements

The authors express their sincere thanks and gratitude to the reviewer for their suggestions toward the improvement of the paper.

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Authors and Affiliations

  1. Department of Mathematics, Arba Minch University, PO BOX – 21, Arbaminch, Ethiopia

    Beyene Chanyalew, Subrata Kumar Sahu & Endalkachew Teshome Ayele

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  1. Beyene Chanyalew
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  2. Subrata Kumar Sahu
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  3. Endalkachew Teshome Ayele
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Correspondence to Subrata Kumar Sahu.

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Chanyalew, B., Sahu, S.K. & Ayele, E.T. Artificial neural networks for the food web model. Eur. Phys. J. Plus 139, 367 (2024). https://doi.org/10.1140/epjp/s13360-024-05107-0

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