• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.295-297
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• 2000

In case of power demand forecasting the most important problem is to deal with the load of special-days, Accordingly, this paper presents a method that forecasting special-days load with regression models and neural networks. Special-days load in summer season was forecasted by the multiple regression models using weekday change ratio Neural networks models uses pattern conversion ratio, and orthogonal polynomial models was directly forecasted using past special-days load data. forecasting result obtains % forecast error of about $1{\sim}2[%]$. Therefore, it is possible to forecast long and short special-days load.

• Asian Journal of Business Environment
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• v.4 no.3
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• pp.27-37
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• 2014

Purpose - In the past, designs for traditional products have usually focused on historic techniques. However, this tradition of using historic techniques has now been replaced by the trend of using the innovative design concept. Research design, data, and methodology - To measure future market trends and quality requirements, we apply the results of the questionnaires and analyze them with various experimental processes and a design methodology. In this way, we gauge the impact of the innovative product value chain on the promotion of new products. Results - Accompanied with an innovative product value chain, the product can stimulate the development of enterprise management, which has become the main issue in social and economic development in every developed country, and can facilitate the progress of enterprise management throughout the enterprise. Conclusions - Customer demand should be emphasized as the primary means to solve design problems, to design optimal solutions, to create differentiation with competitors, and to pursue optimal marketing strategies.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.429-431
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• 2001

The vertically integrated power industry was divided into six generation companies and one market operator, where electricity trading was launched at power exchange. In this environment, the profits of each generation companies are guaranteed according to utilization of their own generation equipments. This paper represents on generator maintenance scheduling and efficient bidding strategies for generation equipments through the calculation of the contract and the application of each generator cost function based on the past demand forecasting error and market operating data.

• International Commerce and Information Review
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• v.6 no.2
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• pp.65-84
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• 2004

Korean Government has provided special support to Korean export industry during past 40 years. However, due to the agreement on UR and appearance of WTO, the Government can't provide most of the subsidies which were allowed before WTO era. Hence, export insurance system became more useful tool since it's one of the few allowed subsidies under WTO. This study tries to find the impacts of export insurance systems on the exports in Korea, the United States, and Japan. Firstly, this study surveyed the export insurance systems of Korea, the United States, and Japan. Then, using a regression analysis it analysed the effects of export insurance systems upon the exports in Korea, the United States, and Japan respectively. The period of data is from 1980 to 1999. The results of the regression analysis for export insurance showed significant and positive effects of both Korean and Japanese but the United States showed insignificant and positive upon the exports.

• Journal of the Korea Safety Management & Science
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• v.19 no.4
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• pp.221-230
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• 2017

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid methods for them are necessary more. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. To measure service quality accurately, this researcher collected and analyzed data by survey for customers who are customers of logistics services, grasped potential satisfaction standard(P) by 5 point Likert scale and one survey for accurate classification of quality attributes through weighted customer satisfaction coefficient changing quality attributes by developing the study on Kano model and Timko's customer satisfaction coefficient, and suggested Potential Customer Satisfaction Improvement index(PCSI) for examining the improvement of customer satisfaction so as to utilize them as an index of differentiated and concrete measurement of service quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1041-1059
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• 2016

The increasing demand from researchers and policy makers for microdata has also increased related privacy and security concerns. During the past two decades, a large volume of literature on statistical disclosure control (SDC) has been published in international journals. This review paper introduces relatively recent SDC approaches to the communities of Korean statisticians and statistical agencies. In addition to the traditional masking techniques (such as microaggregation and noise addition), we introduce an online analytic system, differential privacy, and synthetic data. For each approach, the application example (with pros and cons, as well as methodology) is highlighted, so that the paper can assist statical agencies that seek a practical SDC approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.78-88
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• 2023

The increasing number of technology transfers from public research institutes in Korea has led to a growing demand for patent recommendation platforms for SMEs. This is because selecting the right technology for commercialization is a critical factor in business success. This study developed a patent recommendation system that uses technology transfer data from the past 10 years to recommend patents that are suitable for SMEs. The system was developed in three stages. First, an item-based collaborative filtering system was developed to recommend patents based on the similarities between the patents that SMEs have previously transferred. Next, a content-based recommendation system based on TF-IDF was developed to analyze patent names and recommend patents with high similarity. Finally, a hybrid system was developed that combines the strengths of both recommendation systems. The experimental results showed that the hybrid system was able to recommend patents that were both similar and relevant to the SMEs' interests. This suggests that the system can be a valuable tool for SMEs that are looking to acquire new technologies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.15-20
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• 2020

Recently, the real estate is of high interest. This is because real estate, which was considered only a residential environment in the past, is recognized as a stable investment target due to the ever-growing demand on it. In particular, in the case of the domestic market, despite the decrease in the number of people, the number of single-person households and the influx of people to large cities are accelerating, and real estate prices are rising sharply around the metropolitan area. Therefore, accurately predicting the prospects of the future real estate market becomes a very important issue not only for individual asset management but also for government policy establishment. In this paper, we developed a program to predict future real estate market prices by learning past real estate sales data using machine learning techniques. The data on the market price of real estate provided by the Korea Appraisal Board and the Ministry of Land, Infrastructure and Transport were used, and the average sales price forecast for 2022 by region is presented. The developed program is publicly available so that it could be used in various forms.

• Korean Journal of Social Welfare
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• v.66 no.3
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• pp.133-158
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• 2014

Over the past decades, changes in economic, social and demographic structures have pushed the growth of care employment across countries around the world. Women's increasing labor force participation has squeezed the time so far available for unpaid caregiving and led to increased demand for paid care services. Population aging and increasing needs for pre-school education also have contributed to the growth in demand for care services. As a result, care workers now comprise a large and growing segment of the labor force in many countries including South Korea. But, there are not a few problems. Especially, we take underpaid and undervalued care work very seriously. care work has been generally characterized as underpaid and undervalued compared with other work in developed and developing countries alike. This study tries to show current situation of care work and estimate the wage penalty for doing care work in Korea using official employment micro-data and applying propensity matching analysis. Especially, recent expansion of social service is a big step up for Korean Welfare State. But, there are not a few problems. Especially, we take underpaid and undervalued care work very seriously. This presentation tries to show current situation of care work and estimate the wage penalty for doing care work in Korea using official employment micro-data and applying propensity matching analysis.