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Peer-reviewedCC BYInsects

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

  • Cebrail Barut1
  • Doygun Demirol2
  • Harun Bingöl3
  • Hande Yüksel4
  • Bilal Alatas4
  • İnanç Özgen5
5 affiliations
  1. 1Department of Continuing Education Center, Firat University, Elazig 23119, Türkiye;
  2. 2Department of Computer Technologies, Bingöl University, Bingöl 12000, Türkiye;
  3. 3Department of Software Engineering, Faculty of Engineering and Naturel Sciences, Malatya Turgut Özal University, Malatya 44200, Türkiye;
  4. 4Department of Software Engineering, Faculty of Engineering, Firat University, Elazig 23119, Türkiye; (H.Y.); (B.A.)
  5. 5Department of Bioengineering, Firat University, Elazig 23119, Türkiye
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Cite

BibTeXRIS
BibTeX
@article{barut2026explainable,
  title = {{An Explainable Hybrid Machine Learning Approach Based on MPSO-XGBoost for Pest Density Prediction in Almond Orchards}},
  author = {Cebrail Barut and Doygun Demirol and Harun Bingöl and Hande Yüksel and Bilal Alatas and İnanç Özgen},
  journal = {Insects},
  year = {2026},
  month = sep,
  url = {https://europepmc.org/article/PMC/PMC13705452},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - An Explainable Hybrid Machine Learning Approach Based on MPSO-XGBoost for Pest Density Prediction in Almond Orchards
AU  - Cebrail Barut
AU  - Doygun Demirol
AU  - Harun Bingöl
AU  - Hande Yüksel
AU  - Bilal Alatas
AU  - İnanç Özgen
PY  - 2026
DA  - 2026/09/25
JO  - Insects
UR  - https://europepmc.org/article/PMC/PMC13705452
SN  - 2075-4450
ER  -