• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.1-42
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• 2002

A model to predict population by sex, age and district over a long-range period is proposed based on fuzzy theories. First, a fuzzy model is described. Second, a method to estimate the social increase by sex and age in each district is proposed based on a fuzzy clustering method for dealing with long-range socioeconomic changes in population migration. By the proposed methods, it became possible to predict the population by sex, age and district over a long-range period. Third, the structure and characteristics of the three models of employment model, time distance model, and land use model constructed to predict various socioeconomic indicators, which are require...

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.87-106
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• 2022

Uncertainties in the energy market are increasing due to technology developments (shale revolution), trade wars, COVID-19, and the Russia-Ukraine war. Especially, since 2020, the risk of international trade in the energy market has increased significantly due to changes in the supply chain of transportation and due to prolonged demand reduction because of COVID-19 and the Russian-Ukraine war. Considering these points, this study analyzed connectedness between energy price, tanker index, and uncertainty to understand the connectedness between international trade in the energy market. Main results are summarized as follows. First, as a result of analyzing stable period and unstable period of the energy price model using the MS-VAR model, it was confirmed that both the crude oil market model and the natural gas market model had a higher probability of maintaining stable period than unstable period, increasing volatility by specific events. Second, looking at the results of the analysis of the connectedness between stable period and unstable period of the energy market, it was confirmed that in the case of total connectedness, connectedness between variables was increased in the unstable period compared to the stable period. In the case of the energy market stable period, considering the degree of connectedness, it was confirmed that the effect of the tanker freight index, which represents the demand-side factor, was significant. Third, unstable period of the natural gas market model increases rapidly compared to the crude oil market model, indicating that the volatility spillover effect of the natural gas market is greater when uncertainties affecting energy prices increase compared to the crude oil market.

• The Journal of Information Systems
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• v.32 no.1
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• pp.179-199
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• 2023

Purpose This study builds a prediction model to find stocks that can reach intrinsic value among KOSPI and KOSDAQ-listed companies to improve the stability and profitability of the stock investment. And investment simulations are conducted to verify whether stock investment performance is improved by comparing the prediction model, random stock selection, and the market indexes. Design/methodology/approach Value investment theory and machine learning techniques are applied to build the model. Various experiments find conditions such as the algorithm with the best predictive performance, learning period, and intrinsic value-reaching period. This study selects stocks through the prediction model learned with inventive variables, does not limit the holding period after buying to reach the intrinsic value of the stocks, and targets all KOSPI and KOSDAQ companies. The stock and financial data are collected for 21 years (2001-2021). Findings As a result of the experiment, using the random forest technique, the prediction model's performance was the best with one year of learning period and within one year of the intrinsic value reaching period. As a result of the investment simulation, the cumulative return of the prediction model was up to 1.68 times higher than the random stock selection and 17 times higher than the KOSPI index. The usefulness of the prediction model was confirmed in that the number of intrinsic values reaching the predicted stock was up to 70% higher than the random selection.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.11
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• pp.440-446
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• 1984

This thesis investigates the quantitative aspect of epidemic phenomena utilizing the analytical method of discrete time systems based on the theory of Markov processes. In particular, the pattern on the epidemic character of Influenza was analyzed by the mathematical model of Influenza system, which is derived according to the ecologic relationship between five epidemiolgic states of individuals. The quantitative aspects of the model was characterized by digital computer simulations. The main results were obtained as follows: 1) A Markovian model of influenza system represents accurate spead curve. 2) The latent period of influenza has the standard deviation of 1.98 and also the incubation period is 2.68. 3) If the value of susceptibilities in the pre-epidemic period is less than 20% of the population, the epidemic will occur sporadically. 4) The initial value of susceptibilties obtained by this markov theory is less about 10% of total population than the obtained value according to the deterministic model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.516-519
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• 2012

This study proposes a method of an equivalent bell model in order to tune the beat period of a Korean bell. In a Korean bell having a slight asymmetry, each circumferential mode splits into a mode pair which has a slight difference in frequency, and the interaction of the mode pair makes a beat in vibration and sound. An equivalent bell model which consists of an axi-symmetric bell and an equivalent point mass, has the same mode property as in a real bell. The equivalent bell model is constructed by the finite element analysis based upon the theory of a revolutionary shell Using the equivalent bell model, the beat period is predicted when the bell thickness is locally decreased to improve the beat property. The predicted result is verified by experiment on a test bell. The proposed method is useful to save the time required for tuning the beat period of a large bell.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• The Journal of Fisheries Business Administration
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• v.45 no.2
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• pp.29-38
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• 2014

This study is to analyse the timing of the structural change of price volatility and the asymmetry of price volatility during the period before and after the timing of the structural change of price volatility using Jeju Farming Olive Flounder's production area market price data from January 1, 2007 to June 30, 2013. The analysis methods of Quandt-Andrews break point test and Threshold GARCH model are employed. The empirical results of this study are summarized as follows: First, the result of Quandt-Andrews break point test shows that a single structural change in price volatility occurred on May 4, 2010 over the sample period. Second, during the period before structural change, daily price change rate has averagely positive value which means price increase, but during the period after structural change daily price change rate has averagely negative value which means price decrease. Also, daily volatility of price change rate during the period before structural change is higher than during the period after structural change. This indicates that price volatility decreases after structural change. Third, the estimation results of Threshold GARCH Model show that the volatility response against price increase is larger during the period after structural change than during the period before structural change. Also the result shows the volatility response against price decrease is larger during the period after structural change than during the period before structural change. And, irrespective of the timing of structural change, price increase has an larger effect on volatility than price decrease. This means volatility is asymmetric at price increase.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.47-53
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• 2019

This study examined the effects of risk aversion on the Self-Insurance-cum-Protection activity (SICP) in a two period model, which is in contrast to existing studies that focused on an one period model. The assumption that there is a time difference between making an effort and incurring loss helps examine the effects of risk aversion in the long-term period. An increase in risk aversion always increases the efforts of SICP, whereas existing studies require additional restrictions to both the loss and cost function. Second, an increase in risk aversion always increases the efforts on self-insurance and self-protection. This result is in contrast to that of existing studies in that an increase in risk aversion increases the efforts of self-insurance, whereas the effects on the efforts of self-protection are unclear. Lastly, when there exists a background risk with zero mean and risk aversion increases in a two period model, the prudence condition of the utility function is a sufficient condition to increase the efforts of SICP.

• Korean Journal of Comparative Education
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• v.28 no.4
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• pp.249-272
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• 2018

The purpose of this study is to analyze which group led the process of agenda setting of teacher's certification system in China from 1978 to 2018 using the Cobb & Elder's theoretical model. The period of about 40 years from 1978 to 2018 is divided into the introduction period of teacher's certification period (1978~1992), transition period (1993~1998), and stabilization stage (1999~2018). The agenda setting process was analyzed. As a result, the group that led the process of agenda setting of the Chinese teacher's certification system varied according to the period. The introduction period of teacher's certification system was analyzed as 'Inside Access Model' led by policy makers and government, and the transition period was confirmed as 'Mobilization Model' led by Chinese government and Ministry of Education. The stabilization period was analyzed as 'Outside Initiative Model' led by various groups such as mass media, researchers, and government. It was found that the process of agenda setting of teacher's certification system had been changing toward democratization according to the degree of development of Chinese society, and the quality control of teacher certifications had been strengthened.