• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.445-450
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• 2001

The objective of this study is to develop the GLEAMS-PADDY model for nutrients loading simulation from paddy-field areas. This model is developed by modifying the GLEAMS model. The model is composed of hydrology, sediment and chemical parts. The model was evaluatd using field data. The model estimates water balance and nutrients concentrations reasonably well. The model can be applied to find BMP's in the paddy areas.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.29-39
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• 1995

A model used in the past may be altered at will in modeling for the future. For this situation, the multiprocess dynamic model provides a general framework. In this paper we consider the multiprocess discount normal model with parameters having a time dependent non-linear structure. This model has nice properties such as insensitivity to outliers and quick reaction to abrupt changes of pattern.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.553-561
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• 2012

Various statistical models to Estimate GDP (measured as a nation's economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.117-130
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• 1999

Nayak(1994) suggested a combined randomized response model that combined the Warner's model and greenberg et al.'s model. In this paper we extend Nayak's model to two sample case of including unknown unrelated character also propose some combined models such W-M model and G-M model that modify the Nayak's model. We suggest the efficiency conditions of our models for Nayak's model, also find the efficiency condition of G-M model for the W-M model.

• Korean Management Science Review
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• v.14 no.1
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• pp.131-149
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• 1997

Software cost estimation is an important both for buyers and sellers(developers). We reviewed domestic and foreign researches and practices on software cost estimation with function point method comprehensively, In this paper, we derived four promising alternative function point models. They are an IFPUG(International Function Point User Group)-based model(Model I), a shorthand model for client/sever software systems(Model II), a data-oricnted model for relatively large software projects(Model III), and a general- purpose function point model for non business application softwares as well as business applications(Model IV). Empirical data shows that Model I, II, and IV are very useful function point models. In particular, model II and IV look very useful models since they are concise and accurate. These models can be incorporated in a new improved guideline for software cost estimation. General opinion survey shows that Model I, II and IV are preferable. There are no significant differences in preference between buyers and sellers. The survey also shows that users think function point method is better than step(line of code)-oriented cost estimation methods in many ways including objectivity and estimation accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.75-94
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• 2005

Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.6
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• pp.964-973
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• 1997

A tidal prism eutrophication model, an one-dimensional intertidal model, is developed to study water quality conditions at small coastal basins and tidal creeks. The model simulates the physical transport processes using the concept of tidal flushing. The concept is simple and straightforward, and thus is ideal for small coastal basins with complex geometry. The model, having twenty-four state variables in the water column, simulates salinity, temperature, dissolved oxygen, three algal groups, and the cycles of carbon, nitrogen, phosphorus and silica. The model is applied to the Lynnhaven Bay, a small coastal basin of Chesapeake Bay in U.S.A. The model is calibrated using the field data collected in 1994, and then is verified using the independently collected data in 1980. The model overall gives a good reproduction of the field data, partly owing to the data collected from the field surveys specifically designed for the model application. This paper presents the procedure, and the results of the model calibration and verification.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.135-143
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• 2003

In this study, a real-time simulation model was developed for tracked vehicles with in-arm type semi-active hydro-pneumatic suspension unit using MATLAB S-functions. Since the vehicle model uses relative coordinates and massless link elements, the developed model has an enhanced analytic time performance. Through the comparison of simulation results with multi-body software(DADS), the vehicle model is verified. A controller using on-off skyhook control algorithm is designed with the pilot-centre]led proportional valve based on conventional damper characteristics. Exploiting the developed tracked vehicle model with other subsystem model such as a controller model, a suspension unit model, and a test road model, computer simulations are carried out. Control simulation results with the developed tracked vehicle model show that the semi-active suspension control system has a better performance than the conventional suspension system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.1
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• pp.18-28
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• 2013

It was compared the estimated parameters by the surplus production from three different models, i.e., three types (Schaefer, Gulland, and Schnute) of the traditional surplus production models, a stock production model incorporating covariates (ASPIC) model and a maximum entropy (ME) model. We also evaluated the performance of models in the estimation of their parameters. The maximum sustainable yield (MSY) of small yellow croaker (Pseudosciaena polyactis) in Korean waters ranged from 35,061 metric tons (mt) by Gulland model to 44,844mt by ME model, and fishing effort at MSY ($f_{MSY}$) ranged from 262,188hauls by Schnute model to 355,200hauls by ME model. The lowest root mean square error (RMSE) for small yellow croaker was obtained from the Gulland surplus production model, while the highest RMSE was from Schnute model. However, the highest coefficient of determination ($R^2$) was from the ME model, but the ASPIC model yielded the lowest coefficient. On the other hand, the MSY of Kapenta (Limnothrissa miodon) ranged from 16,880 mt by ASPIC model to 25,373mt by ME model, and $f_{MSY}$, from 94,580hauls by ASPIC model to 225,490hauls by Schnute model. In this case, both the lowest root mean square error (RMSE) and the highest coefficient of determination ($R^2$) were obtained from the ME model, which showed relatively better fits of data to the model, indicating that the ME model is statistically more stable and robust than other models. Moreover, the ME model could provide additional ecologically useful parameters such as, biomass at MSY ($B_{MSY}$), carrying capacity of the population (K), catchability coefficient (q) and the intrinsic rate of population growth (r).

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.178-187
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• 1999

In order to identify a transfer function model with noise, penalty function method has been widely used. In this method, estimation process for possible model parameters from low to higher order proceeds the model identification process. In this study, based on linear estimation method, a new approach unifying the estimation and the identification of ARMAX model is proposed. For the parameter estimation of a transfer function model with noise, linear estimation method by noise separation is suggested instead of nonlinear estimation method. The feasibility of the proposed model identification and estimation method is verified through simulations, namely by applying the method to time series model. In the case of time series model with noise, the proposed method successfully identifies the transfer function model with noise without going through model parameter identification process in advance. A new algorithm effectively achieving model identification and parameter estimation in unified frame has been proposed. This approach is different from the conventional method used for identification of ARMAX model which needs separate parameter estimation and model identification processes. The consistency and the accuracy of the proposed method has been verified through simulations.