Earthquake magnitude estimation using Recursive Least Squares

Younghoon Pyo; Kyunghyun Lee; Kwanho You

doi:10.1109/ICCCBDA.2016.7529590

Earthquake magnitude estimation using Recursive Least Squares

Younghoon Pyo
, Kyunghyun Lee
, Kwanho You

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method is to update the relation between the magnitude and P_d adaptively to predict the magnitude of earthquake more accurately. With the simulation results, we reduced error factors and improved the accuracy of earthquake magnitude estimation.

Original language	English
Title of host publication	Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	394-397
Number of pages	4
ISBN (Electronic)	9781509025930
DOIs	https://doi.org/10.1109/ICCCBDA.2016.7529590
State	Published - 2 Aug 2016
Externally published	Yes
Event	2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016 - Chengdu, China Duration: 5 Jul 2016 → 7 Jul 2016

Publication series

Name	Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016

Conference

Conference	2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016
Country/Territory	China
City	Chengdu
Period	5/07/16 → 7/07/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

earthquake magnitude prediction
error compensation
laser interferometer
recursive least square

Access to Document

10.1109/ICCCBDA.2016.7529590

Cite this

Pyo, Y., Lee, K., & You, K. (2016). Earthquake magnitude estimation using Recursive Least Squares. In Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016 (pp. 394-397). Article 7529590 (Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCBDA.2016.7529590

Pyo, Younghoon ; Lee, Kyunghyun ; You, Kwanho. / Earthquake magnitude estimation using Recursive Least Squares. Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 394-397 (Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016).

@inproceedings{2aec71cc778b4f818670582723aeb464,

title = "Earthquake magnitude estimation using Recursive Least Squares",

abstract = "Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method is to update the relation between the magnitude and Pd adaptively to predict the magnitude of earthquake more accurately. With the simulation results, we reduced error factors and improved the accuracy of earthquake magnitude estimation.",

keywords = "earthquake magnitude prediction, error compensation, laser interferometer, recursive least square",

author = "Younghoon Pyo and Kyunghyun Lee and Kwanho You",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016 ; Conference date: 05-07-2016 Through 07-07-2016",

year = "2016",

month = aug,

day = "2",

doi = "10.1109/ICCCBDA.2016.7529590",

language = "English",

series = "Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "394--397",

booktitle = "Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016",

}

Pyo, Y, Lee, K & You, K 2016, Earthquake magnitude estimation using Recursive Least Squares. in Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016., 7529590, Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016, Institute of Electrical and Electronics Engineers Inc., pp. 394-397, 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016, Chengdu, China, 5/07/16. https://doi.org/10.1109/ICCCBDA.2016.7529590

Earthquake magnitude estimation using Recursive Least Squares. / Pyo, Younghoon; Lee, Kyunghyun; You, Kwanho.
Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 394-397 7529590 (Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Earthquake magnitude estimation using Recursive Least Squares

AU - Pyo, Younghoon

AU - Lee, Kyunghyun

AU - You, Kwanho

PY - 2016/8/2

Y1 - 2016/8/2

N2 - Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method is to update the relation between the magnitude and Pd adaptively to predict the magnitude of earthquake more accurately. With the simulation results, we reduced error factors and improved the accuracy of earthquake magnitude estimation.

AB - Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method is to update the relation between the magnitude and Pd adaptively to predict the magnitude of earthquake more accurately. With the simulation results, we reduced error factors and improved the accuracy of earthquake magnitude estimation.

KW - earthquake magnitude prediction

KW - error compensation

KW - laser interferometer

KW - recursive least square

UR - https://www.scopus.com/pages/publications/84983311729

U2 - 10.1109/ICCCBDA.2016.7529590

DO - 10.1109/ICCCBDA.2016.7529590

M3 - Conference contribution

AN - SCOPUS:84983311729

T3 - Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016

SP - 394

EP - 397

BT - Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016

Y2 - 5 July 2016 through 7 July 2016

ER -

Pyo Y, Lee K, You K. Earthquake magnitude estimation using Recursive Least Squares. In Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 394-397. 7529590. (Proceedings of 2016 IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2016). doi: 10.1109/ICCCBDA.2016.7529590

Earthquake magnitude estimation using Recursive Least Squares

Abstract

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UN SDGs

Keywords

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