Advanced Efficient Feature Selection Integrating Augmented Extreme Learning Machine and Particle Swarm Optimization for Predicting Nitrogen Use Efficiency and Yield in Corn

Advanced Efficient Feature Selection Integrating Augmented Extreme Learning Machine and Particle Swarm Optimization for Predicting Nitrogen Use Efficiency and Yield in Corn

Efficient nitrogen management is crucial for improving corn productivity while minimizing environmental impacts. This study evaluates the response of corn to nitrogen fertilization using three key metrics: yield; nitrogen harvest index (NHI); and agronomic nitrogen use efficiency (ANUE). This experi...

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Bibliographic Details
Main Authors: Josselin Bontemps, Isa Ebtehaj, Gabriel Deslauriers, Alain N. Rousseau, Hossein Bonakdari, Jacynthe Dessureault-Rompré
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Agronomy
Subjects:
augmented extreme learning machine (AELM)
feature selection
particle swarm optimization (PSO)
nitrogen use efficiency (NUE)
soil health indicators
corn yield
Online Access:https://www.mdpi.com/2073-4395/15/1/244
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