Estimation of significant wave height in shallow lakes using the expert system techniques

Abdüsselam Altunkaynak*, Keh Han Wang

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Makalebilirkişi

26 Atıf (Scopus)

Özet

Significant wave height is an important hydrodynamic variable for the design application and environmental evaluation in coastal and lake environments. Accurate prediction of significant wave height can assist the planning and analysis of lake and coastal projects. In this study, the Genetic Algorithm (GA) is used as the optimization technique to better predict model parameters. Also, Kalman Filtering (KF) is used for prediction of significant wave height from wind speed. KF technique makes predictions based on stochastic and dynamic structures. The integrated Geno Kalman Filtering (GKF) technique is applied to develop predictive models for estimation of significant wave height at stations LZ40, L006, L005 and L001 in Lake Okeechobee, Florida. The results show that the GKF methodology can perform very well in predicting the significant wave height and produce lower mean relative error and mean-square error than those from Artificial Neural Network (ANN) model. The superiority of GKF method over ANN is presented with comparisons of predicted and observed significant wave heights.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)2549-2559
Sayfa sayısı11
DergiExpert Systems with Applications
Hacim39
Basın numarası3
DOI'lar
Yayın durumuYayınlandı - 15 Şub 2012

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