Artificial neural network approach for the predicition of the corn (Zea mays L.) leaf area

ODABAŞ M. S., Ergün E., Oner F.

Bulgarian Journal of Agricultural Science, cilt.19, sa.4, ss.766-769, 2013 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 4
  • Basım Tarihi: 2013
  • Dergi Adı: Bulgarian Journal of Agricultural Science
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.766-769
  • Anahtar Kelimeler: Artificial neural network, Corn, Leaf area, Modeling, Zea mays L
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

This research investigates the artificial neural networks utilization in improving leaf area forecasting at corn leaves (Zea mays L.). Best fitting results were obtained with 2 input nodes (leaf length and leaf width), 2 hidden layers and one output (leaf area). Artificial neural network model performance was tested successfully to describe the relationship between actual leaf area and predicted leaf area. R2 of leaf area was 0.98. Artificial neural networks model produced satisfied correlation between measured and predicted value and minimum inspection error.