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

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

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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.

Item Type: Article (Journal)
Additional Information: 6584/29806
Uncontrolled Keywords: Earthquake prediction, Earth Electric field signal, Extended Linear Prediction Coding (LPC), Support Vector Machines (SVM)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr.-Ing. Wahju Sediono
Date Deposited: 14 May 2013 09:15
Last Modified: 26 Mar 2015 10:02
URI: http://irep.iium.edu.my/id/eprint/29806

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