• Management & Information Systems Review
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• v.35 no.3
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• pp.1-22
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• 2016

We analyzed the international comovements and structural changes in the quarterly real GDP by the Markov-switching vector autoregressive model (MS-VAR) from 1971(1) to 2016(1). The main results of this study were as follows. First, the business cycle phenomenon that occurs in the models or individual time series in real GDP has been grasped through the MS-VAR models. Unlike previous studies, this study showed the significant comovements, asymmetry and structural changes in the MS-VAR model using a real GDP across countries. Second, even if there was a partial difference, there were remarkable structural changes in the economy contraction regime(recession), such as 1988(2) ending the global oil shock crisis and 2007(3) starting the global financial crisis by the MS-VAR model. Third, large-scale structural changes were generated in the economic expansion and/or contraction regime simultaneously among countries. We found that the second world oil shocks that occurred after the first global oil shocks of 1973 and 1974 were the main reasons that caused the large-scale comovements of the international real GDP among countries. In addition, the spillover between Korea and 5 countries has been weak during the Asian currency crisis from 1997 to 1999, but there was strong transmission between Korea and 5 countries at the end of 2007 including the period of the global financial crisis. Fourth, it showed characteristics that simultaneous correlation appeared to be high due to the country-specific shocks generated for each country with the regime switching using real GDP since 1973. Thus, we confirmed that conclusions were consistent with a number of theoretical and empirical evidence available, and the macro-economic changes were mainly caused by the global shocks for the past 30 years. This study found that the global business cycles were due to large-scale asymmetric shocks in addition to the general changes, and then showed the main international comovements and/or structural changes through country-specific shocks.

• Environmental and Resource Economics Review
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• v.20 no.3
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• pp.531-565
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• 2011

All previous studies analyzing multivariate time series data of EUA (European Union Allowance) price commonly used endogenous variables within the four variables and included the period from April to June of 2006 in the analysis, when the price distortion occurred. This study uses graph theory and structural vector error correction model (SVECM) to analyze the daily time series data of the EUA (European Union Allowance) price. As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid the EUA price distortion of Phase 1 period (2005~2007). Further, the monthly data including the economic variables as endogenous variables are analyzed.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.51-71
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• 2016

The purpose of this study is to clarify macro causes influencing on the diversity of single-mother households poverty among OECD Countries including Korea. This study carried out pooled time series cross-section analysis applying unbalanced panel design on the period from 1981 to 2012. There is marked diversity on single-mother households poverty. GDP per capita does not contributes to reduce poverty, and female employment rate and % population 0-14 exacerbate poverty. Several factors contribute on poverty reduction including social spending, child cash spending, union density, employment protection on regular workers, proportional representation system, cumulative left cabinet, cumulative women seat. In Korea, it needs to overcome the limit of anti-poverty strategy mainly based on economic growth and labor market flexibility. And it needs to enlarge universal welfare institutions, child benefits, work-family reconciliation policy, and to design adjusted labor market institutions including union density and employment protection, to introduce consensus political model including proportional representation system to enhance left power and women's representation.

• Computational Structural Engineering
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• v.7 no.3
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• pp.95-103
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• 1994

The safety related components in the nuclear power plant should be designed to withstand the seismic load. Among these components the integrity of reactor internals under earthquake load is important in stand points of safety and economics, because these are classified to Seismic Class I components. So far the modelling methods of reactor internals have been investigated by many authors. In this paper, the dynamic behaviour of reactor internals of Yong Gwang 1&2 nuclear power plants under SSE(Safe Shutdown Earthquake) load is analyzed by using of the simpled Global Beam Model. For this, as a first step, the characteristic analysis of reactor internal components are performed by using of the finite element code ANSYS. And the Global Beam Model for reactor internals which includes beam elements, nonlinear impact springs which have gaps in upper and lower positions, and hydrodynamical couplings which simulate the fluid-filled cylinders of reactor vessel and core barrel structures is established. And for the exciting external force the response spectrum which is applied to reactor support is converted to the time history input. With this excitation and the model the dynamic behaviour of reactor internals is obtained. As the results, the structural integrity of reactor internal components under seismic excitation is verified and the input for the detailed duel assembly series model could be obtained. And the simplicity and effectiveness of Global Beam Model and the economics of the explicit Runge-Kutta-Gills algorithm in impact problem of high frequency interface components are confirmed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.45-51
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• 2006

In this paper, we propose a new architecture of Information Granulation based genetically optimized Self-Organizing Fuzzy Polynomial Neural Networks (IG_gSOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially information granulation and genetic algorithms. The proposed IG_gSOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). To evaluate the performance of the IG_gSOFPNN, the model is experimented with using two time series data(gas furnace process and NOx process data).

• Structural Engineering and Mechanics
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• v.54 no.5
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• pp.1017-1044
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• 2015

This study aimed to investigate the random vibration characteristic of train-slab track-bridge interaction system subjected to both track irregularities and earthquakes by use of pseudo-excitation method (PEM). Each vehicle subsystem was modeled by multibody dynamics. A three-dimensional rail-slab- girder-pier finite element model was created to simulate slab track and bridge subsystem. The equations of motion for the entire system were established based on the constraint condition of no jump between wheel and rail. The random load vectors of equations of motion were formulated by transforming track irregularities and seismic accelerations into a series of deterministic pseudo-excitations according to their respective power spectral density (PSD) functions by means of PEM. The time-dependent PSDs of random vibration responses of the system were obtained by step-by-step integration method, and the corresponding extreme values were estimated based on the first-passage failure criterion. As a case study, an ICE3 high-speed train passing a fifteen-span simply supported girder bridge simultaneously excited by track irregularities and earthquakes is presented. The evaluated extreme values and the PSD characteristic of the random vibration responses of bridge and train are analyzed, and the influences of train speed and track irregularities (without earthquakes) on the random vibration characteristic of bridge and train are discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.202-211
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• 2015

Companies build the factory automation system to improve management effectiveness and productivity as prime strategies for sustainable growth. But most companies undergo various trials and errors while carrying out the project without elaborate preparation stage for factory automation. In this study, we tried to verify what factors are critical to effectively building distribution automation system, which is a branch of factory automation system. A consulting model for setting up a Material Handling Automation System by utilizing the Stage-Gate Process, which is product development process was studied. 29 material handling automation projects carried out between the year 1990 to 2013 at K-Company were selected. Interviews with the project managers, operators and maintenance personnels, various records and current status of the projects were used as data for structural equations based on the Milan consulting model and existing researches of factory automation, CIM for material handling automation. Creating effective basis of production, material handling system and energy saving system with expert review, when preparing a material handling automation project, help promote the project planning thus contributing to the performance of the resulting system, which appears though rather weakly in our data. Also the effect of material handling automation can be enhanced through sufficient and effective links to the relevant environments such as production logistics management and automated warehouses. More detailed planning characteristics of project promotion or some time-series data of effective Material Handling Automation System could enhace furthur studies. We propose a consulting model for setting up an efficient material handling automation system.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.703-713
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• 2020

In many geological fields, including hydrogeology, it is of great importance to determine the heterogeneity of the subsurface media. This study briefly introduces the concept and theory of the method that can estimate the hydraulic properties of the media constituting the aquifer, which was recently introduced by Park (2020). After the introduction, the method was applied to the synthetic aquifer to demonstrate the practicality, from which various implications were drawn. The introduced technique uses a global optimization technique called the covariance matrix adaptation evolution strategy (CMA-ES). Conceptually, it is a methodology to characterize the aquifer heterogeneity by assimilating the groundwater level time-series data due to the imposed hydraulic stress. As a result of applying the developed technique to estimate the hydraulic conductivity of a hypothetical aquifer, it was confirmed that a total of 40000 unknown values were estimated in an affordable computational time. In addition, the results of the estimates showed a close numerical and structural similarity to the reference hydraulic conductivity field, confirming that the quality of the estimation by the proposed method is high. In this study, the developed method was applied to a limited case, but it is expected that it can be applied to a wider variety of cases through additional development of the method. The development technique has the potential to be applied not only to the field of hydrogeology, but also to various fields of geology and geophysics. Further development of the method is currently underway.