• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.262-271
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• 2002

This study presents a practical procedure for the Bayesian inversion of geophysical data. We have applied geostatistical techniques for the acquisition of prior model information, then the Markov Chain Monte Carlo (MCMC) method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.55-69
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• 2013

An alternative design method of existing methods based on elastic theory the design method of roadbed considering plastic deformation of roadbed and stress-strain at roadbed materials with the cyclic loading of trains passing. The characteristics of the developed design method considering traffic load, number of cyclic loading and resilience modulus of roadbed materials can evaluate elastic strain as well as plastic settlement with allowable design criteria. The proposed design method is applied to standard roadbed section drawing of HONAM high-speed railway considering design conditions such as allowable elastic and plastic settlement, train speed, the tonnage of trains. As a result, required levels of resilience modulus model parameter ($A_E$), unconfined compressive strength, types of soil material were evaluated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.267-270
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• 2006

The International GNSS Service (IGS) has managed the global GNSS network and provided the highest quality GNSS data and products, which are GPS ephemerides, clock information and Earth orientation parameter, as the standard for GNSS. An important part of its works is to provide the precise orbits of GPS satellites. GPS satellites send their orbit information (broadcast ephemerides) to users and their accuracies are approximately 1.6 meters level, but those accuracies are not sufficient for the high precise applications which require millimeters precision. The current accuracies of the IGS final orbits are within 5 centimeters level and they are used for Earth science, meteorology, space science, and they are made by the IGS analysis centers and combined by the IGS analysis center coordinator. The techniques making the products are very difficult and require the high technology. The Korea Astronomy and Space Science Institute (KASI) studies to make the IGS products. In this study, we developed our own processing strategy and made GPS ephemerides using Bernese GPS software Ver. 5.0. We used the broadcast ephemerides as the initial orbits and processed the globally distributed 150 IGS stations. The result shows about 6 to 8 centimeters in root-mean-squares related to IGS final orbits in each day during a week. We expect that this study can contribute to secure our own high technology.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.171-178
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• 2006

The seismological observation of Korea began in 1905, and has been run with continuous earthquake network of observation, expanding to the advanced country, but still has some problems in accuracy and speed for report. There are many problems to announce the early warning system for earthquakes and tsunami in the East Sea because most events in the East Sea occur outside the seismic network. Therefore multi-waveform data conversion and composition from the surrounding countries such as Korea, Japan and Far East Russia are requested in order to improve more accurate determination of the earthquake parameters. We used FESNET(Far East Seismic Network) technology to analyze the May 29 and June 1 Earthquakes, and the March 20, 2005 Fukuoka Earthquake in this research, using the data sets of KMA, Japan(JMA/MIED) and IRIS stations. It was found out that use of FESNET resulted in more better outputs than that of a single network, either KMA or JMA stations.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.653-664
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• 2010

The land surface reflectance is a key parameter influencing the climate near the surface. Therefore, it must be determined with sufficient accuracy for climate change research. In particular, the characteristics of the bidirectional reflectance distribution function (BRDF) when using earth observation system (EOS) are important for normalizing the reflected solar radiation from the earth's surface. Also, wide swath satellites like SPOT/VGT (VEGETATION) permit sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning. This gives a difficulty to BRDF model based reflectance normalization of high resolution satellites. The principal objective of the study is to add BRDF modeling of high resolution satellites and to supply insufficient angular sampling through identifying BRDF components from SPOT/VGT. This study is performed as the preliminary data for apply to high-resolution satellite. The study provides surface parameters by eliminating BRD effect when calculated biophysical index of plant by BRDF model. We use semi-empirical BRDF model to identify the BRD components. This study uses SPOT/VGT satellite data acquired in the S1 (daily) data. Modeled reflectance values show a good agreement with measured reflectance values from SPOT satellite. This study analyzes BRD effect components by using the NDVI(Normalized Difference Vegetation Index) and the angle components such as solar zenith angle, satellite zenith angle and relative azimuth angle. Geometric scattering kernel mainly depends on the azimuth angle variation and volumetric scattering kernel is less dependent on the azimuth angle variation. Also, forest from land cover shows the wider distribution of value than cropland, overall tendency is similar. Forest shows relatively larger value of geometric term ($K_1{\cdot}f_1$) than cropland, When performed comparison between cropland and forest. Angle and NDVI value are closely related.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.65-65
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• 2019

Near-Earth objects consist of a mixture of bodies originated from outer solar system and main asteroidal belt, which are recognized as comets and near-Earth asteroids. In principal, they have orbits distinguishable by their orbital elements. It is, however, that some comets are recognized as asteroids because they could have lost the most of volatile materials in their subsurface layers. Due to their asteroidal appearances, it has been challenging to discriminate such dormant comets from a list of known asteroids. Here we propose to utilize polarimetric technique for finding such dormant comets. We thus conducted a polarimetric observations of three candidates of dormant comet nuclei, (331471) 1984 QY1, (3552) Don Quixote and (944) Hidalgo, by using the 1.6-m Pirka Telescope at the Nayoro observatory (operated by Hokkaido University, Japan). We selected these asteroids in comet-like orbits (ACOs) based on the orbital elements (i.e., the Tisserand parameter with respect to Jupiter TJ < 3). We found that 1984 QY1 has a polarimetric albedo (geometric albedo determined via polarimetry) pV = 0.16 +/- 0.06 while both Don Quixote and Hidalgo have Rc-band polarimetric albedos pR < 0.05. In accordance with the polarimetric result together with a dynamical analysis, we surmised that 1984 QY1 could be an S-type asteroid evolved into the current orbit via 3:1 mean motion resonance with Jupiter. On the contrary, the previous spectroscopic studies indicated that Don Quixote and Hidalgo are classified into D-type taxonomic group, which are typical of comet nuclei. In this presentation, we will introduce our polarimetric observations of ACOs and emphasize that polarimetry is powerful for discriminating the asteroidal and cometary origins.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.617-628
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• 2021

Drought is a major natural disaster that causes serious social and economic losses. Local drought forecasts can provide important information for drought preparedness. In this study, we propose a new machine learning model that predicts drought by using historical drought indices and meteorological data from 10 sites from 1981 to 2020 in the southeastern part of the Korean Peninsula, Busan-Ulsan-Gyeongnam. Using Bayesian optimization techniques, a hyper-parameter-tuned Random Forest, XGBoost, and Light GBM model were constructed to predict the evaporative demand drought index on a 6-month time scale after 1-month. The model performance was compared by constructing a single site model and a regional model, respectively. In addition, the possibility of improving the model performance was examined by constructing a fine-tuned model using data from a individual site based on the regional model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4C
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• pp.193-200
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• 2010

This study suggests a method predicting at-rest coefficient of earth pressure ($K_0$) in order to evaluate the effect of stress history of granular soil. The method is based on the relation $K_D/K_0={\chi}(E_D/{\sigma}_m{^{\prime}})^{\delta}$, which is developed by combining two previously published relations such as $E_D/{\sigma}_m{^{\prime}}-{\psi}$ and $K_D/K_0-{\psi}$. As $K_D$ and $E_D$ are observed to be sensitive to the pre-stress, both indices are adopted for the estimation of $K_0$ value of granular soil. It is shown that the proposed $K_D/K_0-E_D/{\sigma}_m{^{\prime}}$ relation is insignificantly affected by the stress history. It is concluded from the comparative study that the proposed method, which uses only dilatometer test results to predict the $K_0$ of granular soil, provides more convenient and reliable prediction than other methods which use both CPT and DMT results.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• Journal of the Korean earth science society
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• v.45 no.4
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• pp.349-362
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• 2024

We aimed to evaluate the effectiveness of ensemble optimal interpolation (EnOI) in improving the analysis of significant wave height (SWH) within wave models using satellite-derived SWH data. Satellite observations revealed higher SWH in mid-latitude regions (30° to 60° in both hemispheres) due to stronger winds, whereas equatorial and coastal areas exhibited lower wave heights, attributed to calmer winds and land interactions. Root mean square error (RMSE) analysis of the control experiment without data assimilation revealed significant discrepancies in high-latitude areas, underscoring the need for enhanced analysis techniques. Data assimilation experiments demonstrated substantial RMSE reductions, particularly in high-latitude regions, underscoring the effectiveness of the technique in enhancing the quality of analysis fields. Sensitivity experiments with varying ensemble sizes showed modest global improvements in analysis fields with larger ensembles. Sensitivity experiments based on different decorrelation length scales demonstrated significant RMSE improvements at larger scales, particularly in the Southern Ocean and Northwest Pacific. However, some areas exhibited slight RMSE increases, suggesting the need for region-specific tuning of assimilation parameters. Reducing the observation error covariance improved analysis quality in certain regions, including the equator, but generally degraded it in others. Rescaling background error covariance (BEC) resulted in overall improvements in analysis fields, though sensitivity to regional variability persisted. These findings underscore the importance of data assimilation, parameter tuning, and BEC rescaling in enhancing the quality and reliability of wave analysis fields, emphasizing the necessity of region-specific adjustments to optimize assimilation performance. These insights are valuable for understanding ocean dynamics, improving navigation, and supporting coastal management practices.