STATISTICAL WAVE FORECASTING THROUGH KALMAN FILTERING COMBINED WITH PRINCIPAL COMPONENT ANALYSIS

Proceedings of the International Conference on Coastal Engineering

Noriaki Hashimoto¹  Toshihiko Nagai¹  Masanobu Kudaka² 

[1] Hydrodynamics Laboratory, Marine Environment Division, Port and Harbour Research Institute, Ministry of Transport;Wave Information Laboratory, ECOH Co., Ltd.

关键词: wave forecasting;    Kalman filtering;    principal component analysis;   

DOI  :  10.9753/icce.v26.%p

学科分类：建筑学

来源: Coastal Engineering Research Council

【 摘 要 】

Statistical wave forecasting methods have been applied because of their convenience. Most of them, however, include some drawbacks from the statistical or numerical viewpoints. In this paper, these drawbacks are discussed and a new statistical wave forecasting method utilizing the Kalman filter technique combined with Principal Component Analysis (PCA) is proposed in order to mitigate the drawbacks. The applicability and reliability of the proposed method is examined for five wave observation stations around Japan through simulations based on 5-years of wave data and weather charts.

【 授权许可】

Unknown