• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.497-514
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• 2023

Purpose: This study aims to estimate the demand for various public parking lots in Seoul by clustering similar demand types of parking lots and predicting the demand for new public parking lots. Methods: We examined real-time parking information data and used time series clustering analysis to cluster public parking lots with similar demand patterns. We also performed various regression analyses of parking demand based on diverse heterogeneous data that affect parking demand and proposed a parking demand prediction model. Results: As a result of cluster analysis, 68 public parking lots in Seoul were clustered into four types with similar demand patterns. We also identified key variables impacting parking demand and obtained a precise model for predicting parking demands. Conclusion: The proposed prediction model can be used to improve the efficiency and publicity of public parking lots in Seoul, and can be used as a basis for constructing new public parking lots that meet the actual demand. Future research could include studies on demand estimation models for each type of parking lot, and studies on the impact of parking lot usage patterns on demand.

• Journal of the Korea Safety Management & Science
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• v.12 no.4
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• pp.255-263
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• 2010

The research developes short-run standardized control charts(SSCC) and short-run acceptance control charts(SACC) under the various demand patterns. The demand patterns considered in this paper are three types such as high-variety and repetitive low-volume pattern, extremely-high-variety and nonrepetitive low-volume pattern, and high-variety and extremely-low-volume pattern. The short-run standardized control charts developed by extending the long-run ${\bar{x}}$-R, ${\bar{x}}$-s and I-MR charts have strengths for practioners to understand and use easily. Moreover, the short-range acceptance control charts developed in the study can be efficiently used through combining the functions of the inspection and control chart. The weighting schemes such as Shewhart, moving average (MA) and exponentially weighted moving average (EWMA) can be considered by the reliability of data sets. The two types according to the use of control chart are presented in the short-range standardized charts and acceptance control charts. Finally, process capability index(PCI) and process performance index(PPI) classified by the demand patterns are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.412-421
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• 2013

Motion picture industry is one of the most representative fields in the cultural industry and has experienced constant growth both worldwide and within domestic markets. However, little research has been undertaken for diffusion patterns of motion pictures, whereas various issues such as demand forecasting and success factor analysis have been widely explored. To analyze diffusion patterns, we adopted extended Bass model to reflect the potential demand of movies. Four clusters of selected movies were derived by k-means clustering method with criteria of opening strength and profitability and then compared by their diffusion patterns. Results indicated that movies with high profitability and medium opening strength are most significantly influenced by word of mouth effect, while low profitability movies display nearly monotonic decreasing diffusion patterns with noticeable initial adoption rates and relatively early peak points in their runs.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.71-85
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• 2021

A variety of methods have been proposed through a number of studies on sophisticated demand forecasting models that can reduce logistics costs. These studies mainly determine the applicable demand forecasting model based on the pattern of demand quantity and try to judge the accuracy of the model through statistical verification. Demand patterns can be broadly divided into regularity and irregularity. A regular pattern means that the order is regular and the order quantity is constant. In this case, predicting demand mainly through regression model or time series model was used. However, this demand is called "intermittent demand" when irregular and fluctuating amount of order quantity is large, and there is a high possibility of error in demand prediction with existing regression model or time series model. For items that show intermittent demand, predicting demand is mainly done using Croston or HOLTS. In this study, we analyze the demand patterns of various items of air cargo with intermittent patterns and apply the most appropriate model to predict and verify the demand. In this process, intermittent optimal demand forecasting model of air cargo is proposed by analyzing the fit of various models of air cargo by item and region.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.76-81
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• 2012

The continuing demand for increasingly slimmer and brighter liquid crystal display(LCD) panels has led to an increased focus on the role of the light guide panels(LGPs) or optical films that are used to obtain diffuse, uniform light from the backlight unit(BLU). And the most basic process in the production of such BLU components is the micromachining. LCD BLUs comprise various optical elements such as a LGP, diffuser sheet, prism sheet, and protector sheet with micro patterns. High aspect ratio patterns are required to reduce the number of sheets and enhance light efficiency, but there is a limit to the aspect ratio achievable for a given material and cutting tool. Therefore, this study comprised a series of experimental evaluations conducted to determine the machining feasibility in microcutting various aspect ratio patterns on electroless nickel plated die materials when using single-crystal diamond tools. Cutting performance was evaluated at various cutting speeds and depths of cut using different machining methods and machine tools.

• Journal of the Korea Fashion and Costume Design Association
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• v.10 no.2
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• pp.91-103
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• 2008

Because of comfortable texture and easy treatment, more and more knit products has been required for leisure such as sports, traveling, hobbies, and various social activities. Therefore, the demand of knit is gradually increasing in the clothing industry. There are, however, several issues, which require solutions, and we must develop higher value-added products, which differentiate from those of developing countries allowing us to compete and win in the world market. The patterns on porcelain of underglaze iron, which had been popular from late-l5th century to mid-16th century, are diverse, unique, and traditional--so valuable patterns of our own. The computer hitting machine enables the designer to conceive new designs and produce samples of fabrics within a few minutes, which allows us to save time for mass production. Therefore, it is an essential tool for the knitting industry. After collecting, analyzing, and choosing various patterns on porcelains of underglaze iron, This study reflects the actual experience of hitting the fabrics with the patterns through the computer knitting machine which is also used to produce patterns after designing the new patterns through Adobe Illustrator and Photoshop, which has several merits. This article compares and analyzes them for production, which uses the patterns that has been designed from the patterns on porcelains of underglaze iron.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.3
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• pp.246-255
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• 2023

Due to lack of hydrogen charging stations and hydrogen supply compared to the supply of hydrogen vehicles, social phenomena such as 2-hour queues and restrictions on charging capacity are occurring, which negatively affects the spread of hydrogen vehicles. In order to resolve these problems, it is essential to have a strategic operation of the hydrogen charging stations. To establish operational strategies, it is necessary to derive customer demand patterns and characteristics through the analysis of sales data. This study derived the demand patterns and characteristics of customers visiting hydrogen charging stations through data analysis from various perspectives, such as charging volume, charging speed, number of visits, and correlation with external factors, based on the hydrogen sales data of off-site hydrogen charging stations located in domestic residential areas.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.74-78
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• 2015

With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.

• Journal of the military operations research society of Korea
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• v.5 no.2
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• pp.15-25
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• 1979

Single-period inventory problems such as the newspaper boy problem having quadratic cost functions for both shortages and overage are examined to determine the optimal order level under various principles of choice such as minimum expected cost, aspiration level, and minimax regret. Procedures for finding the optimum order levels are developed for both continuous and discrete demand patterns.