کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1726676 1520757 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evaluating the efficacy of SVMs, BNs, ANNs and ANFIS in wave height prediction
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی دریا (اقیانوس)
پیش نمایش صفحه اول مقاله
Evaluating the efficacy of SVMs, BNs, ANNs and ANFIS in wave height prediction
چکیده انگلیسی

Wave Height (WH) is one of the most important factors in design and operation of maritime projects. Different methods such as semi-empirical, numerical and soft computing-based approaches have been developed for WH forecasting. The soft computing-based methods have the ability to approximate nonlinear wind–wave and wave–wave interactions without a prior knowledge about them. In the present study, several soft computing-based models, namely Support Vector Machines (SVMs), Bayesian Networks (BNs), Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used for mapping wind data to wave height. The data set used for training and testing the simulation models comprises the WH and wind data gathered by National Data Buoy Center (NDBC) in Lake Superior, USA. Several statistical indices are used to evaluate the efficacy of the aforementioned methods. The results show that the ANN, ANFIS and SVM can provide acceptable predictions for wave heights, while the BNs results are unreliable.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Engineering - Volume 38, Issues 2–3, February 2011, Pages 487–497
نویسندگان
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