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Nonstationary prediction of wind and waves in the pacific ocean using fuzzy inference systems

Abstract

In the present paper, ten-year long three-hourly time series of wind and wave data, based on hindcasts of WAVEWATCH III model, are analyzed and modelled as nonstationary stochastic processes. The study area covers the region [100 E, 70 W]x[60 S,66 N]. The initial time series is decomposed by means of the nonstationary modelling, and the residual stationary part is used as input to a Fuzzy Inference System (FIS) in combination with an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of future values of wind and wave parameters. For comparison purposes, the FIS/ANFIS models are also applied to the initial nonstationary series without making any decomposition. The performance of both forecasting procedures is assessed by means of well-known error measures. It should be noted that FIS/ANFIS models are coupled for the first time with a nonstationary time series modelling for forecasting purposes. © Copyright 2016 by the International Society of Offshore and Polar Engineers (ISOPE).

Category

Academic article

Client

  • Research Council of Norway (RCN) / 243814

Language

English

Affiliation

  • SINTEF Ocean / Fisheries and New Biomarine Industry

Year

2016

Published in

ISOPE - International Offshore and Polar Engineering Conference. Proceedings

ISSN

1098-6189

Publisher

International Society of Offshore & Polar Engineers

Volume

2016-January

Page(s)

282 - 289

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