• The Journal of Engineering Geology
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• v.33 no.1
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• pp.1-13
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• 2023

Predicting earthquakes is difficult due to the complexity of the systems underlying tectonic phenomena and incomplete understanding of the interactions among tectonic settings, tectonic stress, and crustal components. The Korean Peninsula is located in a stable intraplate region with a low average seismicity of M 2.3. As public interest in the earthquake grows, we analyzed earthquakes on the Korean Peninsula by attempting to predict spatio-temporal earthquake patterns and magnitudes using Facebook's Prophet model based on deep learning, and here we discuss seismic distribution zones using DBSCAN, a cluster analysis method. The Prophet model predicts future earthquakes in Chungcheongbuk-do, Gyeonggi-do, Seoul, and Gyeongsangbuk-do.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.4 s.50
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• pp.45-54
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• 2006

The characteristics of the ground motion attenuation in Korea and Japan were estimated using the earthquake ground motions recorded at the equal distance observation stations by KMA, K-NET and KiK-net of Korea and Japan. The ground motion attenuation equations proposed for Korea and Japan were evaluated by comparing the predicted value fer the Fukuoka earthquake with the observed records. The predicted value from the attenuation equations shows good agreement with the observed records and each other. It can be concluded from this study that the ground motion attenuation equations developed for Japan can be used usefully for the prediction of a ground motion from far field earthquake more than 200 km and for the evaluation of the far field ground motion attenuation equations proposed fer Korea.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.6
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• pp.277-283
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• 2020

In order to improve the ground-motion prediction equation, which is an important factor in seismic hazard assessment, it is essential to obtain good quality seismic data for a region. The Korean Peninsula has an environment in which it is difficult to obtain strong ground motion data. However, because digital seismic observation networks have become denser since the mid-2000s and moderate earthquake events such as the Odaesan earthquake (Jan. 20, 2007, M_L 4.8), the 9.12 Gyeongju earthquake (Sep. 12, 2016, M_L 5.8), and the Pohang earthquake (Nov. 15, 2017, M_L 5.4) have occurred, some good empirical data on ground motion could have been accumulated. In this study, we tried to build a ground motion database that can be used for the development of the ground motion attenuation equation by collecting seismic data accumulated since the 2000s. The database was constructed in the form of a flat file with RotD50 peak ground acceleration, 5% damped pseudo-spectral acceleration, and meta information related to hypocenter, path, site, and data processing. The seismic data used were the velocity and accelerogram data for events over M_L 3.0 observed between 2003 and 2019 by the Korean National Seismic Network administered by the Korea Meteorological Administration. The final flat file contains 10,795 ground motion data items for 141 events. Although this study focuses mainly on organizing earthquake ground-motion waveforms and their data processing, it is thought that the study will contribute to reducing uncertainty in evaluating seismic hazard in the Korean Peninsula if detailed information about epicenters and stations is supplemented in the future.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.3 s.49
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• pp.65-75
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• 2006

Nonlinear pushover analysis is used to evaluate the earthquake response of building structures. To accurately predict the inelastic response of a structure, the prescribed story load profile should be able to describe the earthquake force profile which actually occurs during the time-history response of the structure. In the present study, a new modal combination method was developed to predict the earthquake load profiles of building structures. In the proposed method, multiple story load profiles are predicted by combining the modal spectrum responses multiplied by the modal combination factors. Parametric studies were performed far moment-resisting frames and walls. Based on the results. the modal combination factors were determined according to the hierarchy of each mode affecting the dynamic responses of structures. The proposed modal combination method was applied to prototype buildings with and without vertical irregularity. The results showed that the proposed method predicts the actual story load profiles which occur during the time-history responses of the structures.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• Structural Engineering and Mechanics
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• v.12 no.1
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• pp.51-69
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• 2001

Whereas the potential of static inelastic analysis methods is recognised in earthquake design and assessment, especially in contrast with elastic analysis under scaled forces, they have inherent shortcomings. In this paper, critical issues in the application of inelastic static (pushover) analysis are discussed and their effect on the obtained results appraised. Areas of possible developments that would render the method more applicable to the prediction of dynamic response are explored. New developments towards a fully adaptive pushover method accounting for spread of inelasticity, geometric nonlinearity, full multi-modal, spectral amplification and period elongation, within a framework of fibre modelling of materials, are discussed and preliminary results are given. These developments lead to static analysis results that are closer than ever to inelastic time-history analysis. It is concluded that there is great scope for improvements of this simple and powerful technique that would increase confidence in its employment as the primary tool for seismic analysis in practice.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.10a
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• pp.369-376
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• 1998

The purpose of the present study is to analyze the response of pipelines subjected to liquefaction-induced permanent ground displacement and to discuss the failure prediction of domestic waterway pipelines. Initially here, characteristics of liquefaction are reviewed and then permanent ground displacement is investigated base on previous earthquake hazard cases. Next, considering the distribution of the transverse permanent ground displacement and equivalent spring constant effect, formulas obtained by a beam theory are established to analyze continuous pipelines. This analysis was performed without consideration of axial effects. So the finite element analysis was used in order to consider the axial stiffness of soil. As a result, degree of liquefaction, width of deformed ground and axial stiffness are crucial points for evaluation the failure of pipelines subjected to permanent ground displacement.

• Structural Engineering and Mechanics
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• v.23 no.2
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• pp.177-193
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• 2006

Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

• Structural Engineering and Mechanics
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• v.5 no.6
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• pp.839-851
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• 1997

Closed-form solutions are analytically derived for stochastic properties of earthquake ground motion fields, which are conditioned by an observed time series at certain observation sites and are characterized by spectra with uncertainties. The theoretical framework presented here can estimate not only the expectations of such simulated earthquake ground motions, but also the prediction errors which offer important information for the field of engineering. Before these derivations are made, the theory of conditional random fields is summarized for convenience in this study. Furthermore, a method for stochastic interpolation of power spectra is explained.