Artificial neural networks for estimation of temporal rate coefficient of equilibrium bar volume

Kankal M., Komurcu M. I., YÜKSEK Ö., AKPINAR A.

INDIAN JOURNAL OF GEO-MARINE SCIENCES, cilt.41, sa.1, ss.45-55, 2012 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 1
  • Basım Tarihi: 2012
  • Dergi Adı: INDIAN JOURNAL OF GEO-MARINE SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.45-55
  • Anahtar Kelimeler: Coastal profiles, Artificial neural network, Temporal variation, Bar volume, Sediment Transport, BEACH PROFILES, PREDICTION, GEOMETRY, MODEL
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

Present study consists the growth of a bar profile caused by cross-shore sediment transport. This is especially on growth of bar volume (V) toward equilibrium bar volume (V-eq). Three analysis methods being a power and linear regression analysis (PRA and LRA) and an Artificial Neural Network (ANN) analysis were performed to determine empirical temporal rate coefficient (alpha). Forty-two experimental data were used for training set and the rest of the experimental data were used for testing set in the ANN analysis. As the results of analyses, the smallest average relative and root mean square error (RMSE) computed for the ANN methods are 7.578% and 0.029, respectively. It has been obtained that the ANN analysis, which is used for determination of a coefficient, gives reasonable results. Finally, bar volumes were calculated by means of computed a values and compared with the results of experimental data.