• Journal of the Korean Regional Science Association
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• v.10 no.2
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• pp.61-71
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• 1994

Despite of being the criteria to choose the efficient and reasonable alternatioves inactual planning process, the measure of accessibility rarely has applied to practices because each model has unexplicity concept of it and limitations in itself. Accessibility implies transportation system which offers opportunity of movement to overcome spatial separation and, simultaneously, land-use system which represents the location of each activity. Therefore, measures of accessibility have to represent the attractiveness of locations and the interactions of activities, that is, land-use and transportation, with an index. Considering that urban activity is based on the economic efficiency, costs and benfits, accessibility means the economic efficiency of the location of activity and the travel in view of land-use and transport repectively. Combined models that measure accessibility with considering land-use and tranportation simultaneously depend on reasonable concepts, but it is too simple for them to explain the accessibility which resulted from complex interaction of urban activities. Combined urban activity model developed by Kim (1983) and Rho (1989) explains the characteristics of activities in each regions and urban strcture in economic general equilibrium states in the long term of urban system. This model measures a regional accessibility with a dual variable which means the location surplus. This is a more systematic and comprehensive model for calculating the regional accessibility because it considers the interaction of each activity in urban system. It needs efforts to apply the accessibility index as a criterion in actual planning process through finding and quantitification of other explanatory variables to measure it in combined urban activity model.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.575-586
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• 2011

In this paper, we study an asymptotic behavior of the finite-time ruin probability of the compound Poisson model in the case that the initial surplus is large. To compare an exact ruin probability with an approximate one, we place the focus on the exact calculation for the ruin probability when the claim size distribution is regularly varying tailed (i.e. exponential claims and inverse Gaussian claims). We estimate an adjustment coefficient in these examples and show the relationship between the adjustment coefficient and the safety premium. The illustration study shows that as the safety premium increases so does the adjustment coefficient. Larger safety premium means lower "long-term risk", which only stands to reason since higher safety premium means a faster rate of safety premium income to offset claims.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Culinary science and hospitality research
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• v.17 no.2
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• pp.168-181
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• 2011

The purpose of this study is to establish an effective marketing strategy as the marketing management strategy by inquiring into the effect of service recovery justice on relationship benefit, relationship satisfaction and long-tenn relationship orientation in food service industry with food service customers. This study showed that the service recovery justice has a positive effect on the relationship benefit according to procedural, interactional and distributive justice, and the customer satisfaction is maximized through the relationship benefit, continuing the relationship as long-tenn friendship customers. That means that despite service companies' many efforts, including the establishment of a goal related to service, as their service failures happen frequently by various internal or external factors, active work is needed through the fair relationship benefit as the service recovery strategy to deal with these service failures positively and keep the customer satisfaction and long-tenn relationship orientation.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1133-1144
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• 2017

Cluster analysis with meteorological data allows to segment meteorological region based on meteorological characteristics. By the way, meteorological observed data are not adequate for cluster analysis because meteorological stations which observe the data are located not uniformly. Therefore the clustering of meteorological observed data cannot reflect the climate characteristic of South Korea properly. The clustering of $5km{\times}5km$ gridded data derived from a numerical model, on the other hand, reflect it evenly. In this study, we analyzed long-term grid data for temperatures and precipitation using cluster analysis. Due to the monthly difference of climate characteristics, clustering was performed by month. As the result of K-Means cluster analysis is so sensitive to initial values, we used initial values with Ward method which is hierarchical cluster analysis method. Based on clustering of gridded data, cluster of meteorological stations were determined. As a result, clustering of meteorological stations in South Korea has been made spatio-temporal segmentation.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.45-52
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• 2020

Since the opening of the national petition site, it has attracted much attention. In this paper, we perform topic analysis of the national petition site and propose a prediction model for answerable petitions based on deep learning. First, 1,500 petitions are collected, topics are extracted based on the petitions' contents. Main subjects are defined using K-means clustering algorithm, and detailed subjects are defined using topic modeling of petitions belonging to the main subjects. Also, long short-term memory (LSTM) is used for prediction of answerable petitions. Not only title and contents but also categories, length of text, and ratio of part of speech such as noun, adjective, adverb, verb are also used for the proposed model. Our experimental results show that the type 2 model using other features such as ratio of part of speech, length of text, and categories outperforms the type 1 model without other features.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.9-18
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• 2006

This paper presents schematically the monitoring system installed in Yongjong Bridge, a self-anchored suspension bridge located in the expressway linking Seoul and Incheon International Airport. Automatic measurement of instrumented civil engineering structures is now widely applied for behavior monitoring during construction in field as well as long-term monitoring for lifetime assessment of bridge structures. A representative example of results that can be acquired through structural health monitoring system is presented by means of data measured during a few years after the opening of the bridge. In order to effectively measure the tension force for hangers that have relatively short length or high tension force, a static tension measurement device has been explored. Newly equipped railway system on the existing bridge results in change of dead load, consequently dynamic characteristics have also been changed. This result can be detected by the monitoring system during and after railway construction.

• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.6
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• pp.480-494
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• 2009

Long term extreme wave data are essential for planning and designing coastal structures. Since the availability of the field data for the waters around Korean peninsula is limited to provide a reliable wave statistics, the wave climate information has been generated by means of long-term wave hindcasting using available meteorological data. KORDI(2005) has proposed extreme wave data at 106 stations off the Korean coast from 1979 to 2003. In this paper, extreme data sets of wave(KORDI, 2005) have been analyzed for best-fitting distribution functions, for which the spread parameter proposed by Goda(2004) is evaluated. The calculated values of the spread parameter are in good agreement with the values based on method of moment for parameter estimation. However, the spread parameter of extreme wave data has a representative value ranging from about 1.0 to 2.8 which is larger than some foreign coastal waters, it is necessary to review deep water design wave.