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Author

Cebrail Barut

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Open access Sep 2026

An Explainable Hybrid Machine Learning Approach Based on MPSO-XGBoost for Pest Density Prediction in Almond Orchards

Accurate prediction of pest density and population levels in almond production is of great importance for crop yield, the prevention of quality losses, and the effectiveness of integrated pest management (IPM) strategies. Complex feature interactions in agricultural field data can affect both the predictive performance...

Cebrail Barut, Doygun Demirol, Harun Bingol et al. · 0 citations
Open access Sep 2026

RF-SPEA2 Hybrid Rule Inference and Optimization Architecture

The high predictive performance of machine learning models in complex classification tasks often comes with limited transparency, particularly for black-box models whose decision processes cannot be directly inspected. In this study, a two-stage Random Forest–SPEA2 hybrid rule inference and optimization architecture is...

Cebrail Barut · 0 citations

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