• 한국시뮬레이션학회논문지
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• 제17권3호
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• pp.19-26
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• 2008

본 논문에서는 중기 국채(Treasure Note; T-Note)의 실제 자료를 이용하여 채권 가격에 대한 이자율을 예측하는 동적인 예측 알고리즘을 제안하고 있다. 제안한 알고리즘은 이자율 기간 구조를 근본으로 하고 있으며 표준 위너 과정(standard Wiener process)과 같은 다양한 금융 모형의 대안으로 활용 가능하다. 본 논문에서는 실제 자료의 누적 분포 함수(Cumulative Distribution Function; CDF)를 이용하여 이자율을 측정하였으며 CDF는 수치적 방법인 보간법 중에 자주 활용되는 내츄럴 큐빅 스플라인(natural cubic spline; NCS)방법을 통하여 얻었다. 위에서 얻은 CDF를 통하여 난수 생성기법(random number generation scheme; RNGS)을 이용하여 채권의 가격를 계산하였다. 컴퓨터 시뮬레이션을 통해 얻은 실험결과로부터 제안된 예측 알고리즘에서 엄밀도(precision)의 낮은 값을 얻음으로써 채권의 가치가 더욱 예리하고 정확하게 평가되었음을 확인할 수 있었으며, 이는 매우 근거 있는 예측이라 할 수 있다.

• 한국재난정보학회 논문집
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• 제3권1호
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• pp.37-53
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• 2007

Various difficult problems occur due to insufficient bearing capacity or excessive settlements when constructing roads or large complexes. Accurate predictions on the final settlement and consolidation time can help in choosing the ground improvement method and thus enables to save time and expense of the whole project. Asaoka's method is probably the most frequently used for settlement prediction which are based on Terzaghi's one dimensional consolidation theory. Empirical formulae such as Hyperbolic method and Hoshino's method are also often used. However, it is known that the settlement predicted by these methods do not match with the actual settlements. Furthermore these methods cannot be used at design stage when there is no measured data. To find an elaborate method in predicting settlement in embankments using various test results and actual settlement data from domestic sites, Back-Propagation Neural Network(BPNN) and Recurrent Neural Network(RNN) were employed and the most suitable model structures were obtained. Predicted settlement values by the developed models were compared with the measured values as well as numerical analysis results. Analysis of the results showed that RNN yielded more compatible predictions with actual data than BPNN and predictions using cone penetration resistance were closer to actual data than predictions using SPT results. Also, it was found that the developed method were very competitive with the numerical analysis considering the number of input data, complexity and effort in modelling. It is believed that RNN using cone penetration test results can make a highly efficient tool in predicting settlements if enough field data can be obtained.

• 통상정보연구
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• 제10권2호
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• pp.325-348
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• 2008

The purpose of this study is to find out the relationship between job fitness, organizational justice(distributive, procedural, interactional), job satisfaction, organizational trust, organizational commitment, and voluntary turnover intention in private organization such as in small fire in Korea. To identify the these relationships, the secondary data or past studies that were related with job fitness, organizational justice, job satisfaction, organizational trust, organizational commitment, voluntary turnover intention was collected and theoretically arranged. I made the theoretical proposed model to explain these relationships between the constructs, identify the operational definitions and 18 hypotheses was established, there was executed the survey of 262 in employees. Using the collected data, previous performances to confirm the construct validity and internal consistency by EFA(Exploratory Factor Analysis); i.e. factor analysis by SPSS, reliability by cronbach's a, and by the CFA(Confirmative Factor Analysis) and structural equations modelling the proposed model was tested by LISREL v. 8.52. The research came to the conclusions as follows: First, three perceived justice had the positive effect to the job satisfaction empirically. Second, procedural justice in three perceived justice only had the positive effect to the organizational trust empirically. Third, distributive justice in three perceived justice only had the positive effect to the organizational commitment empirically. Forth, job fitness had the positive effect to the organizational commitment, organizational trust, job satisfaction empirically in perspective. Fifth, I found the relationship between job satisfaction and organizational commitment, between job satisfaction and organizational trust was positive, between organizational commitment and trust. Finally, job satisfaction, organizational trust had not the positive effect directly, but indirect effect via organizational commitment was identified in voluntary turnover intention by empirical test.

• 한국소음진동공학회논문집
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• 제15권12호
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• pp.1389-1397
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• 2005

Since blast-induced vibration may cause serious problem to the rock mass as well as the nearby structures, the prediction of blast-induced nitration and the stability evaluation must be performed before blasting activities. Dynamic analysis has been increased recently in order to analyze the effect of the blast-Induced vibration. Most of the previous studies, however, were based on the continuum analysis unable to consider rock joints which significantly affect the wave propagation and attenuation characteristics. They also adopted pressure corves estimated tv theoretical or empirical equations as input detonation load, thus there were very difficult to reflect the characteristics of propagating media. In this study, therefore, we suggested a dynamic distinct element analysis technique which uses velocity waveform obtained from a test blast as an input detonation load. A distinct element program, UDEC was used to consider the effect of rock joints. In order to verify the validity of proposed method, the test blast was simulated. The predicted results from the proposed method showed a good agreement with the measured vibration data from the test blast. Through the dynamic numerical modelling on the planned road tunnel and slope, we evaluated the effect of blast-induced nitration and the stability of rock slope.

• 한국물환경학회지
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• 제24권1호
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• pp.7-18
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• 2008

The objective of this study was to develop and apply a water quality simulation model for the evaluation of ungaged watershed. The Modified WASP5 consisted of three sub-models, LOAD-M, DYN-M, and EUT-M. LOAD-M, an empirical model, estimates runoff loadings using point and non-point source data of villages. Daecheong Dam watershed was selected for the research to calibrate, verify and application of Modified-WASP5. LOAD-M model was established using field data collected from all items of water quality and water quantity gaging stations of the watersheds, and was applied to the ungauged watersheds, taking the watershed properties under consideration. The result of water quality simulation using ModifiedWASP5 shows that the observed BOD data of Yongpo and Daechong Dam in 1999 were 0.8 mg/L and 1.0 mg/L, and simulated data were 0.9 mg/L and 0.9 mg/L, respectively. In case of 1999, average BOD concentrations were 0.8 mg/L and 1.0 mg/L. Simulated concentration showed 1.1 mg/L and 1.5 mg/L, respectively. Generally, the simulation results were in good agreement with the observed data. This study was focused on formulating an integrated model for evaluating ungauged watersheds. Even though simulation results varied slightly due to limited availability of data, the model developed in this study would be a useful tool for the assessment and management of ungauged watersheds.

• 한국정보시스템학회지:정보시스템연구
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• 제29권1호
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.

• Journal of Power Electronics
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• 제11권5호
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• pp.759-766
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• 2011

This paper focuses on monitoring and predicting the short circuit faults of the rotor windings of large turbo-generator systems. For the purpose of increasing efficiency and decreasing maintenance cost, a method that combines the HHT (Hilbert Huang Transform) with a wavelet has been studied. This method is based on analyzing a classical Albright detecting coil. Due to the Empirical Mode Decomposition (EMD) and the Intrinsic Mode Functions (IMF) of the HHT the exact location of a short circuit of rotor windings may be given. However, a part of the useful information is eliminated by the unreasonable decomposing scale of the wavelet. Based on the thermodynamics modeling method, this study was illustrated with a 50MW turbo-generator system that is installed in Northern China. The analysis results, which have very good agreement with those of a previous study, show that the method of combining the HHT with a wavelet is an effective way to analyze and predict the short circuit faults of the rotor windings of large generators, such as supercritical turbo-generator systems and wind turbo-generator systems. This work can offer a useful reference for analyzing smart grids by improving the power quality of a distribution network that is supplied by a turbo-generator system.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.778-804
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• 2017

Software today has become an inseparable part of our life. In order to achieve the ever demanding needs of customers, it has to rapidly evolve and include a number of changes. In this paper, our aim is to study the relationship of object oriented metrics with change proneness attribute of a class. Prediction models based on this study can help us in identifying change prone classes of a software. We can then focus our efforts on these change prone classes during testing to yield a better quality software. Previously, researchers have used statistical methods for predicting change prone classes. But machine learning methods are rarely used for identification of change prone classes. In our study, we evaluate and compare the performances of ten machine learning methods with the statistical method. This evaluation is based on two open source software systems developed in Java language. We also validated the developed prediction models using other software data set in the same domain (3D modelling). The performance of the predicted models was evaluated using receiver operating characteristic analysis. The results indicate that the machine learning methods are at par with the statistical method for prediction of change prone classes. Another analysis showed that the models constructed for a software can also be used to predict change prone nature of classes of another software in the same domain. This study would help developers in performing effective regression testing at low cost and effort. It will also help the developers to design an effective model that results in less change prone classes, hence better maintenance.

• Journal of Korea Trade
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• 제24권8호
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• pp.81-100
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• 2020

Purpose - Based on complexity theory, this study develops a configurational model to predict the profitability of Halal cosmetics firms in the Indonesian and Malaysian markets. The proposed research model involves two level configurations-industry context and selling strategies-to predict high and low scores of a firm's profitability. The industry context configuration model comprises industry stability, product homogeneity, price sensitivity, and switching cost. Selling strategies include customer-focused, competitor-focused, and margin-focused approaches. Design/methodology - This is the first empirical study that calculates causal models using a combination of industry context and selling strategy factors to predict profitability. Data obtained from the marketing managers of cosmetics firms are used to test the proposed configurational model using fuzzy-set qualitative comparative analysis (fsQCA). It contributes to the current knowledge of business marketing by identifying the factors necessary to achieve profitability using analysis of condition (ANC). Findings - The results revealed that unique and distinct models explain the conditions for high and low profitability in the Indonesian and Malaysian halal cosmetic markets. While customer-focused selling strategy is necessary to attain a higher profit in both the markets, margin-focused selling strategy appears to be an essential factor only in Malaysia. Complexity of the interactions of selling strategies with industry factors and differences between across two study markets confirmed that complexity theory can support the research configurational model. The theoretical and practical implications are also illustrated. Originality/value - Despite the rapid growth of the global halal industry, there is little knowledge about the halal cosmetic market. This study contributes to the current literature of the halal market by performing a set of asymmetric analytical approaches using a complex theoretical model. It also deepens our understating of how the Korean firms can approach the Muslim consumer's needs to generate more beneficial turnover/revenue.

• Ocean Systems Engineering
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• 제9권3호
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• pp.287-328
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• 2019

Comprehensive understanding of the flood risk assessments via frequency analysis often demands multivariate designs under the different notations of return periods. Flood is a tri-variate random consequence, which often pointing the unreliability of univariate return period and demands for the joint dependency construction by accounting its multiple intercorrelated flood vectors i.e., flood peak, volume & durations. Selecting the most parsimonious probability functions for demonstrating univariate flood marginals distributions is often a mandatory pre-processing desire before the establishment of joint dependency. Especially under copulas methodology, which often allows the practitioner to model univariate marginals separately from their joint constructions. Parametric density approximations often hypothesized that the random samples must follow some specific or predefine probability density functions, which usually defines different estimates especially in the tail of distributions. Concentrations of the upper tail often seem interesting during flood modelling also, no evidence exhibited in favours of any fixed distributions, which often characterized through the trial and error procedure based on goodness-of-fit measures. On another side, model performance evaluations and selections of best-fitted distributions often demand precise investigations via comparing the relative sample reproducing capabilities otherwise, inconsistencies might reveal uncertainty. Also, the strength & weakness of different fitness statistics usually vary and having different extent during demonstrating gaps and dispensary among fitted distributions. In this literature, selections efforts of marginal distributions of flood variables are incorporated by employing an interactive set of parametric functions for event-based (or Block annual maxima) samples over the 50-years continuously-distributed streamflow characteristics for the Kelantan River basin at Gulliemard Bridge, Malaysia. Model fitness criteria are examined based on the degree of agreements between cumulative empirical and theoretical probabilities. Both the analytical as well as graphically visual inspections are undertaken to strengthen much decisive evidence in favour of best-fitted probability density.