Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination

The ability of the signal processing techniques to predict earthquakes may help to reduce the catastrophic effect of the earthquake. The earth's electric field signal is one of the features that can be used to predict the earthquakes (EQs) by analyzing the changes in its characteristic prior th...

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Main Authors:	Astuti, Winda, Sediono, Wahju, Akmeliawati, Rini, Salami, Momoh Jimoh Emiyoka
Format:	Article
Language:	English
Published:	Universal Association of Computer and Electronics Engineers 2013
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/29806/ http://irep.iium.edu.my/29806/ http://irep.iium.edu.my/29806/4/p.ijcsia.2013.journal.ses.astuti.pdf

id	iium-29806
recordtype	eprints
spelling	iium-298062015-03-26T02:02:05Z http://irep.iium.edu.my/29806/ Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination Astuti, Winda Sediono, Wahju Akmeliawati, Rini Salami, Momoh Jimoh Emiyoka TK7885 Computer engineering The ability of the signal processing techniques to predict earthquakes may help to reduce the catastrophic effect of the earthquake. The earth's electric field signal is one of the features that can be used to predict the earthquakes (EQs) by analyzing the changes in its characteristic prior the earthquake. The signal is extracted using extended Linear Predictive Coding (LPC). This approach is based on the projection of the excitation signal on the right eigenvectors impulse response of the LPC filter. The resulting projected value is weighted by corresponding singular value, leading to an approximate sum of exponentially damped sinusoids (EDS). The extracted vector is used as input of the prediction system in order to determine the location of the incoming earthquake. Support vector machines (SVMs) method is applied as classification technique. The basic idea of SVMs is mapping non-linear training data into higher-dimensional feature space through the kernel function. This paper presents a detailed analysis of the earth’s electric field signal due to earthquakes which occurred in Greece. The earthquake occurred during 2008 is used as model to train the system and some of the earthquakes that happened between 2003 and 2010 are used to evaluate the performance of the proposed system. The result shows good accuracy of 96.67% for training phase and 77.8% for the testing phase. Universal Association of Computer and Electronics Engineers 2013-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/29806/4/p.ijcsia.2013.journal.ses.astuti.pdf Astuti, Winda and Sediono, Wahju and Akmeliawati, Rini and Salami, Momoh Jimoh Emiyoka (2013) Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination. UACEE International Journal of Advances in Computer Science and its Applications, 3 (2). pp. 269-272. ISSN 2250 – 3765 http://ijcsia.uacee.org/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Astuti, Winda Sediono, Wahju Akmeliawati, Rini Salami, Momoh Jimoh Emiyoka Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
description	The ability of the signal processing techniques to predict earthquakes may help to reduce the catastrophic effect of the earthquake. The earth's electric field signal is one of the features that can be used to predict the earthquakes (EQs) by analyzing the changes in its characteristic prior the earthquake. The signal is extracted using extended Linear Predictive Coding (LPC). This approach is based on the projection of the excitation signal on the right eigenvectors impulse response of the LPC filter. The resulting projected value is weighted by corresponding singular value, leading to an approximate sum of exponentially damped sinusoids (EDS). The extracted vector is used as input of the prediction system in order to determine the location of the incoming earthquake. Support vector machines (SVMs) method is applied as classification technique. The basic idea of SVMs is mapping non-linear training data into higher-dimensional feature space through the kernel function. This paper presents a detailed analysis of the earth’s electric field signal due to earthquakes which occurred in Greece. The earthquake occurred during 2008 is used as model to train the system and some of the earthquakes that happened between 2003 and 2010 are used to evaluate the performance of the proposed system. The result shows good accuracy of 96.67% for training phase and 77.8% for the testing phase.
format	Article
author	Astuti, Winda Sediono, Wahju Akmeliawati, Rini Salami, Momoh Jimoh Emiyoka
author_facet	Astuti, Winda Sediono, Wahju Akmeliawati, Rini Salami, Momoh Jimoh Emiyoka
author_sort	Astuti, Winda
title	Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
title_short	Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
title_full	Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
title_fullStr	Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
title_full_unstemmed	Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
title_sort	earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination
publisher	Universal Association of Computer and Electronics Engineers
publishDate	2013
url	http://irep.iium.edu.my/29806/ http://irep.iium.edu.my/29806/ http://irep.iium.edu.my/29806/4/p.ijcsia.2013.journal.ses.astuti.pdf
first_indexed	2023-09-18T20:43:47Z
last_indexed	2023-09-18T20:43:47Z
_version_	1777409539492020224

Earthquake prediction system based on the earth’s electric field signal prior to the earthquake: location determination

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