The Advantages of Artifical Neural Networks to Give Length-Weight Relations and Comparison of Growth

Cigsar B., YELDAN H., ÜNAL D.

INTERNATIONAL JOURNAL OF ECOLOGICAL ECONOMICS & STATISTICS, cilt.43, sa.2, ss.35-48, 2022 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 43 Sayı: 2
  • Basım Tarihi: 2022
  • Dergi Adı: INTERNATIONAL JOURNAL OF ECOLOGICAL ECONOMICS & STATISTICS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), EconLit, Pollution Abstracts, zbMATH
  • Sayfa Sayıları: ss.35-48
  • Anahtar Kelimeler: Artifical neural networks, Gompertz models, logistic models, pelates quadrilineatus, schnute models, MULTIMODEL INFERENCE, FISH GROWTH, 1ST RECORD, MODELS, SELECTION, MEGALOPS, PREDICT
  • Çukurova Üniversitesi Adresli: Evet

Özet

This study has two main purposes. The first one is to compare the performances of Logistics, Gompertz, Schnute and von Bertalanfy models according to the determination coefficient (R-2) and Mean Squared Error criteria, and these comparisons are aimed to be discussed in terms of gender.