Statistical wave forecasting through Kalman filtering combined with principal component analysis

Noriaki Hashimoto; Toshihiko Nagai; Masanobu Kudaka

Statistical wave forecasting through Kalman filtering combined with principal component analysis

Noriaki Hashimoto, Toshihiko Nagai, Masanobu Kudaka

Research output: Contribution to journal › Conference article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	1364-1377
Number of pages	14
Journal	Proceedings of the Coastal Engineering Conference
Volume	2
Publication status	Published - 1998
Externally published	Yes
Event	Proceedings of the 1998 26th International Conference on Coastal Engineering, ICCE-98 - Copenhagen, Denmark Duration: Jun 22 1998 → Jun 26 1998

All Science Journal Classification (ASJC) codes

Ocean Engineering

Cite this

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abstract = "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.",

author = "Noriaki Hashimoto and Toshihiko Nagai and Masanobu Kudaka",

year = "1998",

language = "English",

volume = "2",

pages = "1364--1377",

journal = "Proceedings of the Coastal Engineering Conference",

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note = "Proceedings of the 1998 26th International Conference on Coastal Engineering, ICCE-98 ; Conference date: 22-06-1998 Through 26-06-1998",

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T1 - Statistical wave forecasting through Kalman filtering combined with principal component analysis

AU - Hashimoto, Noriaki

AU - Nagai, Toshihiko

AU - Kudaka, Masanobu

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

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M3 - Conference article

AN - SCOPUS:0032259871

SN - 0893-8717

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SP - 1364

EP - 1377

JO - Proceedings of the Coastal Engineering Conference

JF - Proceedings of the Coastal Engineering Conference

T2 - Proceedings of the 1998 26th International Conference on Coastal Engineering, ICCE-98

Y2 - 22 June 1998 through 26 June 1998

ER -

Statistical wave forecasting through Kalman filtering combined with principal component analysis

Abstract

All Science Journal Classification (ASJC) codes

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