• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.3
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• pp.160-170
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• 2016

In this study, the bottom tracking observation in the tidal entrance within Mokpo coast is performed using ADCP in order to estimate net flux of water mass and tidal prism. First of all, observed rawdata was conducted coordinate rotation considering rotation of the cross-section in order to derive the predominant velocity component. And observed rawdata is converted into Sigma coordinate with normalization and blank zone data near the water surface and bottom is interpolated using von-Karman equation. Net flux of water mass is calculated quantitively from the interpolated data, calculated results show that these represent well characteristic of ebb superiority at Mokpo coast as well as change of net flux of water mass with tide. Also, by complementing the definition of tidal prism proposed in past studies, the definition of tidal prism including tidal condition was re-established. Based on the new definition, tidal prism at a tidal entrance using bottom tracking data with ADCP is estimated quantitively for the first time domestically. The results are compared with those for results of previous study, calculated results were in good agreement with previous studies.

• Water for future
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• v.14 no.4
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• pp.35-52
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• 1981

This study is to evaluate the areal precipitation from the basic data groups of monthly, seasonal, and annual rainfalls over all ma in stations in Korea. The evaluating pocesses are performed through the point and regional frequency analysis from the basic data. The basic data groups are divided into two periods-the first(1916-1944) and the second (1960-1979)-which are compared with each other. In the point frequecny analysis, the variable transformation method is applied to the best fitting distribution, and the normal fittings are established by using the Chisquare test method. In the regional frequency analysis, the geomorphologic factors and hydrometeorological factors are taken into consideration when dividing into five zones and Thiessen method and the Isohyetal method are applied. The results of this study are as follows: 1)The areal precipitation values of the first period are about 70-80mm less than that of the second period for the whole of Korea. Therefore, a new precipitation value of 1180mm is considered more suitable than the value of 1159mm, which has been up till now. 2)As the annual areal precipitiation values areevaluated over the five divide zones, it tis noticed that the difference between the values of the first period and the second is the largest in spring (to the extent of 5 times that in the other seasonas). Thereform it is considered that this result is necessary for the establishment of a timely insurance plan for the water resources. 3)The application of the Isohyetal method through the division of Korea into five zones is considered to be a reasonable procedure in the analysis of areal precipitation.

• Journal of the Korean Regional Science Association
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• v.38 no.2
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• pp.43-57
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• 2022

The Land Suitability Assessment is mandatory by National Land Planning and Utilization Act and the results are considered in the establishment of urban master plan and urban management plan. The study aims to examine whether the application of Land Suitability Assessment in developed urban areas is appropriate. A simulation analysis based on the Seoul's data of environmental ecological, physical, and spatial characteristics was conducted on urban green, the only applicable land for the assessment in Seoul. The results of the assessment shows that all pieces of lands in urban green is suitable for 'development'. This conflicts to the purpose of land use of urban green which needs to be conserved to protect the natural environment and landscape, animals and plants, environmental pollution, and urban sprawl. In the analysis applying optional indicators such as the distance from the area of Biotope Class 1 to prevent this conflict, the results shows little difference. This supports the necessity to review this regulation including an option to exclude developed urban areas such as Seoul in the assessment.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.