Wind direction forecasting with artificial neural networks and support vector machines

The authors propose two methods for short term forecasting of wind direction with the aim to provide input for tactic decisions during yacht races. The wind direction measured in the past minutes is used as input and the wind direction for the next two minutes constitutes the output. The two methods are based on artificial neural networks (ANN) and support vector machines (SVM), respectively. For both methods they optimise the length of the moving average that they use to pre-process the input data, the length of the input vector and, for the ANN only, the number of neurons of each layer. The forecast is evaluated by looking at the mean absolute error and at a mean effectiveness index, which assesses the percentage of times that the forecast is accurate enough to predict the correct tactical choice in a sailing yacht race. The ANN forecast based on the ensemble average of ten networks shows a larger mean absolute error and a similar mean effectiveness index than the SVM forecast. However, the authors showed that the ANN forecast accuracy increases significantly with the size of the ensemble. Therefore increasing the computational power, it can lead to a better forecast.

• Record URL:
  • https://doi.org/10.1016/j.oceaneng.2014.12.026
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0029801814004831
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Tagliaferri, F
  • Viola, I M
  • Flay, R G J
• Publication Date: 2015-3-15

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; References;
• Pagination: pp 65-73
• Serial:
  • Ocean Engineering
  • Volume: 97
  • Issue Number: 0
  • Publisher: Pergamon
  • ISSN: 0029-8018
  • EISSN: 1873-5258
  • Serial URL: http://www.sciencedirect.com/science/journal/00298018

Subject/Index Terms

• TRT Terms: Maneuvering; Neural networks; Sailing ships; Weather forecasting; Wind; Yachts
• Uncontrolled Terms: Support vector machines; Yacht racing
• Subject Areas: Environment; Marine Transportation; Planning and Forecasting; Vehicles and Equipment; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01557802
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 25 2015 4:20PM