• 한국태양에너지학회:학술대회논문집
• /
• 2009.11a
• /
• pp.205-210
• /
• 2009

Generally, the building's windows and ventilation for the purpose of mining and the vista and windows by emotional engineering design area is a growing trend. According to the flow of energy is lost from the building, will be achieved through the walls and roof and windows. Among these, the window through the loss of about 45% of the entire building is big enough to rate. In addition, the building regulation U-value Limitation of window is $3.3W/m^2$ K in southern regions, while U-value Limitation of wall is $0.35{\sim}0.58W/m^2$ K. It means that the energy loss through windows is six times more than it through wall. Therefore, the purpose of this study is to evaluate the environmental performance of the super window system by verification experiment. The results of this study are as follows; 1)Thermal performance of insulated Super Window measured as $1.44W/m^2$ $^{\circ}C$ 2)Required energy for heating was cut down about 5.3% from 266.99 $MJ/m^2$ yr to 252.85 $MJ/m^2$ yr 3)Super Window's reduction rates increased 4.1% from 31.48% to 35.58% when it is compared to normal windows. 4)Building energy efficiency rating elevated from 2nd rating to 1st rating.

• KIEAE Journal
• /
• v.10 no.4
• /
• pp.19-28
• /
• 2010

As design tools, building performance certification systems can be applied to provide adequate guidelines on design process to create environment-friendly buildings. Domestic certification systems of residential building took effect by doing supply to designers and contractors from affiliated organization of governments in the early 2000s. As a result, Building Energy Rating System, Apartment Performance Rating System, Green Homes and other means to promote green designs have been operated. International trends of applying certification systems were started in the early 1990s as forms of LEED in USGBC, BREEAM in BRE, GBTool Canada. These systems aim to evaluate building performance in line with the Climatic Change Convention and realize sustainable building design. In 2009, residential buildings accounted for the largest portion of the internal real estate market with 67.9 percent according to the National Statistical Office data. And for 18 years since 1991, apartments among constructed residential buildings have ranked top taking up 77.7% as of 2009. Apartment performance evaluations accordingly are to promote to constitution of improving tenant quality of life, the residential environment and saving energy and resources in the internal building market. The purpose of this study is to compare and analyze valuation bases of each sector in evaluation systems of residential buildings at home and abroad to upgrade current systems through reflecting the characteristics of residential buildings. Implementation of this study basically include comparison of valuation bases and partial analysis on properties of rating systems to suggest requisites for improvement in building performance certification.

• KDI Journal of Economic Policy
• /
• v.28 no.1
• /
• pp.1-47
• /
• 2006

Even after significant changes in the financial market due to the financial crisis the corporate debt markets have seen created turmoil caused such as by Daewoo, Hyundai, and credit card companies in the financial system. These lagging improvements of corporate debt markets are mainly due to inadequate market infrastructure. Specifically, the credit rating agencies have not been successful in providing proper and timely information on the loan repayment abilities of debtors. This study analyzes past performance of credit rating agencies in Korea and tries to develop policy implications to improve the role of credit rating agencies based on the recent discussions on credit rating agencies by academics and the SEC. In addition, this study focuses on unique operation environments of Korean credit rating agencies, which have kept credit rating agencies from providing fair, timely, and useful information. To warrant proper operation of credit rating agencies, it is essential to cope with unique problems in Korean credit rating agencies. We classify the unique problems of Korean credit rating agencies into ownership and governance structure, conflict of interests due to ancillary fee-based business, legal recognition of credit rating in the court, and code of conduct problem, etc. and propose policy directions to improve the quality and credibility of credit ratings.

• Journal of the Korean Society for Advanced Composite Structures
• /
• v.1 no.1
• /
• pp.34-45
• /
• 2010

This paper describes the design, manufacturing process, testing, application, and assessment of capacity-ratings of the first all advanced composites bridge on a public highway system. In order to verify the bridge design prior to the field application, a sub-scale bridge superstructure was built and tested in the laboratory. The field load test results were compared with those of the finite element analysis for the verification of validity. To investigate its in-service performance, field load testing and visual inspections were conducted under an actual service environment. The paper includes the presentation and discussion for advanced composites bridge capacity rating based on the stress modification coefficients obtained from the test results. The test result indicates that the advanced composites bridge has no structural problems and is structurally performing well in-service as expected. Since these composite materials are new to bridge applications, reliable data is not available for their in-service performance. The results may provide a baseline data for future field advanced composites bridge capacity rating assessments and also serve as part of a long-term performance of advanced composites bridge.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.213-225
• /
• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1997.10a
• /
• pp.173-176
• /
• 1997

In this paper, the classification performances of inductive learning methods are investigated using the credit rating data. The adopted classifiers are Multiple Discriminant Analysis (MDA), C4.5 of Quilan, Multi-Layer Perceptron (MLP) and Cascade Correlation Network (CCN). The data used in this analysis is obtained using the publicly announced rating reports from the three korean rating agencies. The performances of 4 classifiers are analyzed in term of prediction accuracy. The results show that no classifier is dominated by the other classifiers.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.679-683
• /
• 2005

The technique which connects Generalized Regression Neural Networks Model(GRNNM) with Genetic Algorithm (CA) is used to derive rating curve in the river basin. GRNNM architecture consists of 4 layers ; input, hidden, summation and output layer. GA method is applied to estimate the optimal smoothing factor when GRNNM is trained. The derivation of rating curve using GRNNM is considered different kinds of hydraulic characteristics such as water stage, area and mean velocity and is applied two stage stations; Sunsan and Jungam. Furthermore, it is compared with conventional curve-fitting method. Through the training and validation performance, the results show that GRNNM is much superior as compared to the conventional curve-fitting method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.11a
• /
• pp.612-615
• /
• 2006

In this study, we compared and analyzed the floor impact noise insulation performance produced by the rating methods. The rating methods are using reversed A-weighting curve, A-weighted sound pressure levels(dB(A)). The results of this study are(1)dB(A) by the specified frequency is 0.5dB(A) at light weight and 2.5dB(A) at heavy weight upper than all pass dB(A)(2)the rating using reversed A-weighting curve is 5dB lower than dB(A)(3)the number of rating using reversed A-weighting curve mainly depends on impact noise pressure level of 63Hz in heavy weight but dB(A) does not.

• Proceedings of the SAREK Conference
• /
• 2009.06a
• /
• pp.3-8
• /
• 2009

Since 2001, the Building Energy Efficiency Rating and Certification System have been implemented in Korea. For rating the energy efficiency performance, the evaluation tool for Building Energy Efficiency Rating System has been used. In this study, the evaluation tool was compared with detailed analysis programs(Trnsys 16, ESP-r) through simulations of heating energy needs for apartment, and we checked the character of the evaluation tool.

• Journal of Information Processing Systems
• /
• v.13 no.5
• /
• pp.1358-1371
• /
• 2017

Dynamic thermal rating (DTR) system is an effective method to improve the capacity of existing overhead line. According to the methodology based on CIGRE (International Council on Large Electric systems) standard, ampacity values under steady-state heating balance can be calculated from ambient environmental conditions. In this study, simulation analysis of relations between parameters and ampacity is described as functional dependence, which can provide an effective basis for the design and research of overhead transmission lines. The simulation of ampacity variation in different rating scales is described in this paper, which are determined from real-time meteorological data and conductor state parameters. To test the performance of DTR in different rating scales, capacity improvement and risk level are presented. And the experimental results show that the capacity of transmission line by using DTR has significant improvement, with low probability of risk. The information of this study has an important reference value to the operation management of power grid.