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arXiv · 2511.16676

Fractional Artificial Neural Networks for Growth Models

Juan Carlos Najera-Tinoco·Martin P. Arciga-Alejandre·Jorge Sanchez-Ortiz·Francisco J. Ariza-Hernandez
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Abstract

In this paper we present a method to solve initial value problems for fractional growth models, such as generalizations of the exponential and logistic with periodic harvesting models. Using a discretization of the Caputo derivative we propose a fractional artificial neural network, which is implemented in the statistical software R. Moreover, we show examples where the analytical solutions and the approximation of the artificial neural network are compared.

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Juan Carlos Najera-Tinoco, Martin P. Arciga-Alejandre, Jorge Sanchez-Ortiz, Francisco J. Ariza-Hernandez. 2025-11-08. Fractional Artificial Neural Networks for Growth Models. https://arxiv.org/abs/2511.16676

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