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Application of Fuzzy Time Series Techniques in Wind and Wave Data Forecasting

[+] Author Affiliations
Christos N. Stefanakos, Grim Eidnes

SINTEF Materials and Chemistry, Trondheim, Norway

Orestis Schinas

Hamburg School of Business Administration, Hamburg, Germany

Paper No. OMAE2014-24612, pp. V04BT02A046; 9 pages
doi:10.1115/OMAE2014-24612
From:
  • ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 4B: Structures, Safety and Reliability
  • San Francisco, California, USA, June 8–13, 2014
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-4543-1
  • Copyright © 2014 by ASME

abstract

This work explores the applicability of widely known fuzzy time series forecasting techniques for the prediction of wind and wave data. These techniques have extensively been used with great success to the forecasting of stock prices. In the present work, long-term time series of wind speed, significant wave height, and peak period are examined and used for the verification of the forecasting performance of the fuzzy models. To examine the forecasting accuracy, the root mean squared error (RMSE) is used as an evaluation criterion to compare the forecasting performance of the listing models. As the importance of quality of wind and wave data increases, effective forecasting could further benefit designers of offshore structures and environmental researchers.

Copyright © 2014 by ASME
Topics: Waves , Time series , Wind

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