• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.27-35
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• 2013

In this study, we developed the trial product on 3D magnetic inversion tentatively named 'KMag3D'. Also, we briefly introduced its own function and graphic user interface on which especially focused through the development in the form of user manual. KMag3D is consisted of two fundamental frame for the 3D magnetic inversion. First, algebraic reconstruction technique was selected as a 3D inversion algorithm instead of least square method conventionally used in various magnetic inversion. By comparison, it was turned out that algebraic reconstruction algorithm was more effective and economic than that of least squares in aspect of both computation time and memory. Second, for the effective determination of the 3D initial and a-priori information model required in the execution of our algorithm, we proposed the practical technique based on the assemblage of 2D forward modeling and inversion results for individual user-selected 2D profiles. And in succession, initial and a-priori information model were constructed by appropriate interpolation along the strke direction. From this, we concluded that our technique is both suitable and very practical for the application of 3D magentic inversion problem.

• Geophysics and Geophysical Exploration
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• v.2 no.1
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• pp.43-53
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• 1999

Numerical modeling and inversion for electromagnetic exploration methods are essential to understand behaviour of electromagnetic fields in complex subsurface. In this study, a finite element method was adopted as a numerical scheme for the 2.5-dimensional forward problem. And a finite element equation considering linear conductivity variation was proposed, when 2.5-dimensional differential equation to couple eletric and magnetic field was implemented. Model parameters were investigated for near-field with large source effects and far-field with responses dominantly by homogeneous half-space. Numerical responses by this study were compared with analytic solutions in homogeneous half-space. Blocky inversion model was modified to be applied to the forward calculation in this study and it was also adopted in the inversion algorithm. Resolution for isolated bodies were investigated to confirm possibility and limitation of inversion for electromagnetic exploration data.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.3-47
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• 2021

Recently a multilayer spectral inversion (MLSI) model has been proposed to infer the physical parameters of plasmas in the solar chromosphere. The inversion solves a three-layer radiative transfer model using the strong absorption line profiles, H alpha and Ca II 8542 Å, taken by the Fast Imaging Solar Spectrograph (FISS). The model successfully provides the physical plasma parameters, such as source functions, Doppler velocities, and Doppler widths in the layers of the photosphere to the chromosphere. However, it is quite expensive to apply the MLSI to a huge number of line profiles. For example, the calculating time is an hour to several hours depending on the size of the scan raster. We apply deep neural network (DNN) to the inversion code to reduce the cost of calculating the physical parameters. We train the models using pairs of absorption line profiles from FISS and their 13 physical parameters (source functions, Doppler velocities, Doppler widths in the chromosphere, and the pre-determined parameters for the photosphere) calculated from the spectral inversion code for 49 scan rasters (~2,000,000 dataset) including quiet and active regions. We use fully connected dense layers for training the model. In addition, we utilize a skip connection to avoid a problem of vanishing gradients. We evaluate the model by comparing the pairs of absorption line profiles and their inverted physical parameters from other quiet and active regions. Our result shows that the deep learning model successfully reproduces physical parameter maps of a scan raster observation per second within 15% of mean absolute percentage error and the mean squared error of 0.3 to 0.003 depending on the parameters. Taking this advantage of high performance of the deep learning model, we plan to provide the physical parameter maps from the FISS observations to understand the chromospheric plasma conditions in various solar features.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.361-371
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• 2009

Resistivity tomography is very effective geophysical method to find out the resistivity distribution and its change in time around a tunnel. Thus, the resistivity tomogram can provide helpful information which is necessary for the effective maintenance of the tunnel. However, an air filled tunnel severely distorts tomography data, especially when the current or potential electrode is placed near the tunnel. Moreover, the distortion can often lead to misinterpretation of tomography monitoring data. To solve these problem, we developed a resistivity modeling and time-lapse inversion program which include a tunnel. In this study, using the developed program we assured that the inversion including a tunnel gives much more accurate image around a tunnel, compared with the conventional tomogram where the tunnel is not included. We also confirmed that the time-lapse inversion of resistivity monitoring data defines well resistivity changed areas around a tunnel in time.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.7-17
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• 2011

We have developed an inversion code for three-dimensional (3D) resistivity tomography including the anisotropy effect. The algorithm is based on the finite element approximations for the forward modelling and Active Constraint Balancing method is adopted to enhance the resolving power of the smoothness constraint least-squares inversion. Using numerical experiments, we have shown that anisotropic inversion is viable to get an accurate image of the subsurface when the subsurface shows strong electrical anisotropy. Moreover, anisotropy can be used as additional information in the interpretation of subsurface. This algorithm was also applied to the field dataset acquired in the abandoned old mine area, where a high-rise apartment block has been built up over a mining tunnel. The main purpose of the investigation was to evaluate the safety analysis of the building due to old mining activities. Strong electrical anisotropy has been observed and it was proven to be caused by geological setting of the site. To handle the anisotropy problem, field data were inverted by a 3D anisotropic tomography algorithm and we could obtain 3D subsurface images, which matches well with geology mapping observations. The inversion results have been used to provide the subsurface model for the safety analysis in rock engineering and we could assure the residents that the apartment has no problem in its safety after the completion of investigation works.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.69-76
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• 2022

The traveling salesman problem(TSP) is one of the most famous combinatorial optimization problem. So far, many metaheuristic search algorithms have been proposed to solve the problem, and one of them is local search. One of the very important factors in local search is neighbor generation method, and random-based neighbor generation methods such as inversion have been mainly used. This paper proposes 4 new greedy-based neighbor generation methods. Three of them are based on greedy insertion heuristic which insert selected cities one by one into the current best position. The other one is based on greedy rotation. The proposed methods are applied to first-choice hill-climbing search and simulated annealing which are representative local search algorithms. Through the experiment, we confirmed that the proposed greedy-based methods outperform the existing random-based methods. In addition, we confirmed that some greedy-based methods are superior to the existing local search methods.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.175-191
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• 2002

The equations of a polar fluid of hydromagnetic fluctuating through a porous medium axe cast into matrix form using the state space and Laplace transform techniques the resulting formulation is applied to a variety of problems. The solution to a problem of an electrically conducting polar fluid in the presence of a transverse magnetic field and to a problem for the flow between two parallel fixed plates is obtained. The inversion of the Laplace transforms is carried out using a numerical approach. Numerical results for the velocity, angular velocity distribution and the induced magnetic field are given and illustrated graphically for each problems.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.371-383
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• 2001

In this survey article, we shall introduce the applications of the theory of reproducing kernels to inverse problems. At the same time, we shall present some operator versions of our fundamental general theory for linear transforms in the framework of Hilbert spaces.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.221-230
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• 2021

This paper proposes full waveform inversion (FWI) for estimating the physical properties of a layered half-space. An FWI solution is obtained using a genetic algorithm (GA), which is a well-known global optimization approach. The dynamic responses of a layered half-space subjected to a harmonic vertical disk load are measured and compared with those calculated using the estimated physical properties. The responses are calculated using the thin-layer method, which is accurate and efficient for layered media. Subsequently, a numerical model is constructed for a layered half-space using mid-point integrated finite elements and perfectly matched discrete layers. An objective function of the global optimization problem is defined as the L2-norm of the difference between the observed and estimated responses. A GA is used to minimize the objective function and obtain a solution for the FWI. The accuracy of the proposed approach is applied to various problems involving layered half-spaces. The results verify that the proposed FWI based on a GA is suitable for estimating the material properties of a layered half-space, even when the measured responses include measurement noise.