• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.641-651
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• 2003

This study suggests the hybrid models for interest rate forecasting using structural changes (or change points). The basic concept of this proposed model is to obtain significant intervals caused by change points, to identify them as the change-point groups, and to reflect them in interest rate forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in the U. S. Treasury bill rate dataset. The second phase is to forecast the change-point groups with data mining classifiers. The final phase is to forecast interest rates with backpropagation neural networks (BPN). Based on this structure, we propose three hybrid models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported model, (2) case-based reasoning (CBR)-supported model, and (3) BPN-supported model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the prediction ability of hybrid models to reflect the structural change.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.203-211
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• 2009

Korean public owners who order public multi-family housing construction projects have yet to gain access to a model for predicting construction cost. For this reason, their construction cost prediction is mainly dependent upon historic data and experience. In this paper, a cost-prediction model based on Case-Based Reasoning (CBR) in the design phase of public multi-family housing construction projects was developed. The developed model can determine the total construction cost by estimating the different Building, Civil, Mechanical, Electronic and Telecommunication, and Landscaping work costs. Model validation showed an accuracy of 97.56%, confirming the model's excellent viability. The developed model can thus be used to predict the construction cost to be shouldered by public owners before the design is completed. Moreover, any change orders during the design phase can be immediately applied to the model, and various construction costs by design alternative can be verified using this model. Therefore, it is expected that public owners can exercise effective design management by using the developed cost prediction model. The use of such an effective cost prediction model can enable the owners to accurately determine in advance the construction cost and prevent increase or decrease in cost arising from the design changes in the design phase, such as change order. The model can also prevent the untoward increase in the duration of the design phase as it can effectively control unnecessary change orders.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.57-72
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• 2003

This article provides integrated neural network models for the interest rate forecasting using change-point detection. The model is composed of three phases. The first phase is to detect successive structural changes in interest rate dataset. The second phase is to forecast change-point group with data mining classifiers. The final phase is to forecast the interest rate with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the predictability of integrated neural network models to represent the structural change.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.731-738
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• 2010

Cavitation is described by formation and collapse of the bubbles in a liquid when the ambient pressure decreases. Formed bubbles grow and collapse by change of pressure, and when they collapse, shockwave by high pressure is generated. In general, bubble behavior can be described by Rayleigh-Plesset equation under adiabatic or isothermal condition and hence, phase shift by the pressure change in a bubble cannot be considered in the equation. In our study, a numerical model is developed from the mathematical model considering the phase shift from the previous study. In the developed numerical model, size of single spherical bubble is calculated by the change of mass calculated from the change of the ambient pressure in a liquid. The developed numerical model is verified by a case of liquid flow in a narrow channel.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.153-166
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• 2003

This study presents the time-divided forecasting model to integrate evolutionary optimization algorithm and change point detection based on artificial neural networks (ANN) for the prediction of (Korea) stock price index. The genetic algorithm(GA) is introduced as an evolutionary optimization method in this study. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as optimal or near-optimal change point groups, and to use them in the forecasting of the stock price index. The proposed model consists of three phases. The first phase detects successive change points. The second phase detects the change-point groups with the GA. Finally, the third phase forecasts the output with ANN using the GA. This study examines the predictability of the proposed model for the prediction of stock price index.

• Journal of Science Education
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• v.34 no.1
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• pp.47-57
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• 2010

The purpose of this study was to investigate how the lesson using the newly developed Phase Change Model of Venus can change ninth graders' geocentrical concept related to the progression of the phase of Venus. In order to know students' concept change of the progression of the phases of Venus, test sheets and a questionnaire regarding solar systems were developed and used pre and post test. The results showed that many students have an astronomical preconception of geocentricism, and some students have an especially poor scientific understanding of the solar system. However, there were significant changes in students' conceptual levels (p<.05) after teaching with the Venus's Phase Change Model. Therefore, teaching with the Phase Change Model of Venus was effective on students' scientific conceptual change from geocentricism to heliocentricism.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.543-556
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• 2001

This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.10 no.1
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• pp.12-21
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• 1981

The Enthalpy Model was verified in order to analyze two- dimensional phase change problems. By using the Enthalpy Model, interface locations, frozen fraction rates, heat flux distribution rut cooled surfaces, and surface-integrated heat flux were purely numerically calculated in rectangular thermal storage units, whose initial condition was saturated liquid and phase change material was cooled on its boundaries by convective heat transfer. The calculations were performed for various Stefan numbers and Biot numbers. The effect on those dimensionless numbers were explained.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.556-565
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• 1995

The physical model of interest is based upon the concentric cylinder, where the outside cylinder is filled with optically thick and high temperature phase change material(PCM). The fluid is flowing through the inside cylinder to transfer the appropriate energy. The fluid is flowing through the inside cylinder to transfer the appropriate energy. The governing equations for the phase change material including internal thermal radiation and for the turbulent transfer fluid have been employed and numerically solved. The optically thick phase change justifies the P-l spherical harmonics approximation, which is believed to be appropriate choice particularly for the much coupled problem like in this study. The solid/liquid interface, temperature distribution within the PCM and the heat flux from the PCM to the transfer fluid have been obtained and compared with those of laminar transfer fluid. The numerical results show that the turbulent transfer fluid accelerates the solid/liquid interface and results in the increase of heat transfer rate from the PCM. The internal thermal radiation within the PCM, however, does not always playa role to increase the heat transfer rate throughout the inside cylinder. It is believed that the combined heat flux has been picked up more in the inflowing area than in the pure conductive phase change material.

• The KSFM Journal of Fluid Machinery
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• v.14 no.6
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• pp.45-53
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• 2011

Multiphase lattice Boltzmann method (LBM) has been used to simulate the nucleate pool boiling directly. For the phase change model, the thermal model and the Stefan boundary condition were introduced to the isothermal LBM. The phase change model was validated by the bubble growth in a superheated liquid under no gravity. The bubble growth on and departure from a superheated wall has been simulated successfully. The preliminary results showed that the detail process of nucleate pool boiling was in good agreement with the experimental results.