Kıyıya Dik Kum Barlarının Bitiş Noktasının Yapay Zeka Yöntemleriyle Tahmini

Öz

Kıyıya dik katı madde sonucu oluşan kumbar parametrelerinin tahmini, kıyı yapılarının tasarımı için oldukça önemlidir. Bu çalışmada, kıyıya dik kum barlarının bitiş noktasının kıyı çizgisine olan mesafesi (Xs) tahmini için deneysel veriler kullanılmıştır. Deneylerde 5 farklı ortalama tane çapı d₅₀=0,25, 0,32, 0,45, 0,62 ve 0,80 mm ve 1/8, 1/10 ve 1/15 olmak üzere 3 farklı taban eğimi kullanılmıştır. Bar bitiş noktasının kıyı çizgisine olan mesafesinin tahmini için farklı kıyı eğimleri, farklı tane çaplarındaki kıyı malzemeleri, farklı dalga periyodu ve dalga dikliği girdi parametresi olarak kullanılarak çoklu doğrusal regresyon, destek vektör regresyonu, basit üyelik fonksiyonları ve bulanık kural oluşturma tekniği (Simple Membership Functions and Fuzzy Rule Generation Technique–SMRGT) ve uyarlamalı ağ tabanlı sistemi yöntemleri ile modeller oluşturulmuştur. Model sonuçlarına göre uyarlamalı ağ tabanlı bulanık çıkarım sistemi modelinin diğer iki modele göre daha düşük hata değerleri verdiği ve determinasyon katsayısına göre daha başarılı olduğu görülmüştür.

Anahtar Kelimeler

• Kıyıya Dik Sediment Taşınımı
• Bar Parametreleri
• Bulanık Mantık
• Anfis
• Çoklu Doğrusal Regresyon
• Support Vector Regresyonu

Estimation of Ending points of Cross-Shore Sandbars using Artificial Inteligence Method

Öz

Abstract: Estimation of sandbar parameters occured by cross-shore sediment transport is very important for the design of coastal structures. In this study, the experimental data utilized to estimate the distance of the ending point of cross-shore sandbars (Xs). In the experiments, 5 different average grain diameters d₅₀=0.25, 0.32, 0.45, 0.62 and 0.80 mm and 3 different base slopes of 1/8, 1/10 and 1/15 were used. Multiple linear regression, Sequential Minimal Optimization algorithm for support vector machine Regression, Simple Membership Functions and Fuzzy Rule Generation Technique (SMRGT) and Adaptive neuro fuzzy inference system were used to estimate the ending point of cross-shore ending bars to the shoreline using input parameters as different coastal slopes, different sediment diameters, different wave periods and wave steepness. According to the model results, it was seen that the adaptive network-based fuzzy inference system model was more successful than the other three models with lower error values and higher coefficient of determination.

Anahtar Kelimeler

• Cross-shore sediment transport
• bar parameter
• fuzzy logic
• anfis
• multi linear regression
• support vector regression.

Kaynakça

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