Prediction of cross-shore sandbar volumes using neural network approach
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Dosyalar
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Japan Kk
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Correct estimation of bar volumes, wave height, wave period and median sediment diameter is crucial for the designing of coastal structures and water quality problem. In this study, bar volumes caused by cross-shore sediment transport were investigated using a physical model and obtained 64 experimental data considering the wave steepness (H (0)/L (0)) and period (T), the bed slope (m) and the sediment diameter (d (50)). Artificial neural network (ANN) and multi-linear regression (MLR) are used for predicting the bar volumes. A multi layer perceptron is used as the ANN structure. The results show that the ANN model estimates are much closer to the experimental data than the MLR model estimates.
Açıklama
Anahtar Kelimeler
Artificial neural networks (ANN), Multi-linear regression (MLR), Bar volumes, Cross-shore sediment transport, Coastal dynamics
Kaynak
Journal of Marine Science and Technology
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
20
Sayı
1
