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  • 标题:Application of neural networks and support vector machine for significant wave height prediction
  • 本地全文:下载
  • 作者:Jadran Berbić ; Eva Ocvirk ; Dalibor Carević
  • 期刊名称:Oceanologia
  • 印刷版ISSN:0078-3234
  • 出版年度:2017
  • 卷号:59
  • 期号:3
  • 页码:331-349
  • DOI:10.1016/j.oceano.2017.03.007
  • 出版社:Elsevier B.V.
  • 摘要:For the purposes of planning and operation of maritime activities, information about wave height dynamics is of great importance. In the paper, real-time prediction of significant wave heights for the following 0.5-5.5h is provided, using information from 3 or more time points. In the first stage, predictions are made by varying the quantity of significant wave heights from previous time points and various ways of using data are discussed. Afterwards, in the best model, according to the criteria of practicality and accuracy, the influence of wind is taken into account. Predictions are made using two machine learning methods - artificial neural networks (ANN) and support vector machine (SVM). The models were built using the built-in functions of software Weka, developed by Waikato University, New Zealand.
  • 关键词:Significant wave height; Wave prediction; Machine learning; ANN; SVM
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