A deep learning-based model for the propagation mechanism of southern corn rust

Keqin Su; Alain Miranville; Jie Cao; Xinguang Yang; Keqin Su; Alain Miranville; Jie Cao; Xinguang Yang

doi:10.3934/era.2026075

Electronic Research Archive

2026, Volume 34, Issue 3: 1653-1670. doi: 10.3934/era.2026075

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Research article

A deep learning-based model for the propagation mechanism of southern corn rust

1.
College of Information and Management Science, Henan Agricultural University, China
2.
Department of Mathematics and Statistics, Henan Normal University, Xinxiang 453007, China
3.
Laboratoire de Mathématiques Appliqués du Havre, Université Le Havre Normandie, Le Havre 76600, France

Received: 15 December 2025 Revised: 09 February 2026 Accepted: 11 February 2026 Published: 27 February 2026

A new mathematical model based on differential equations and deep learning is proposed to study the propagation mechanism of southern corn rust (SCR). Equilibrium and stability analyses of system are conducted in detail. Compared with the quantitative assessment of SCR, numerical parameter estimation and the corresponding interpretation are given.
- southern corn rust,
- mathematical modeling,
- deep learning
Citation: Keqin Su, Alain Miranville, Jie Cao, Xinguang Yang. A deep learning-based model for the propagation mechanism of southern corn rust[J]. Electronic Research Archive, 2026, 34(3): 1653-1670. doi: 10.3934/era.2026075

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Abstract

A new mathematical model based on differential equations and deep learning is proposed to study the propagation mechanism of southern corn rust (SCR). Equilibrium and stability analyses of system are conducted in detail. Compared with the quantitative assessment of SCR, numerical parameter estimation and the corresponding interpretation are given.

References

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