• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1839-1843
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• 2007

현재 우리나라는 100년이 넘는 수문관측에도 불구하고 수문자료의 양과 질이 선진국에 비해 부족하며, 이를 해결하기 위해 IHP유역, 하천 시험유역 운영 등 각종 수문조사 사업을 시행하고 있다. 정확하고 신뢰성 있는 유량자료의 확보는 각종 수공구조물 설계, 하천의 이 치수 계획의 수립, 홍수 예 경보 시스템의 분석을 위한 기본적이고도 중요한 과정이다. 본 연구에서는 만경강 유역에 위치하고 있는 목천, 하리, 봉동, 소양, 효자지점을 대상유역으로 선정하고 2006년 저 평수기 및 홍수기에 걸쳐 유량을 측정하여 자료를 확보하였다. 측정된 성과의 적절성 검토를 위해 최대구간유량비와 불확실도를 산정하여 신뢰하였고 이들의 수리특성을 분석하였다. 일반적으로 수자원 분야에서 유출을 검토하기 위해 수위자료가 아닌 유량자료를 이용하여 해당 분야에 대한 분석을 시행한다. 이에 본 연구에서는 대상유역의 측정 성과를 바탕으로 수위-유량관계 곡선식을 개발하고 수위 수문곡선을 유량 수문곡선으로 변환하였다. 또한 유출특성을 분석하기 위해 연 유출률 분석, 상 하류 유량검토, 호우사상별 직접유출률 분석을 실시하였다. 그 결과 만경강 유역의 지점별 연 유출률은 하리 69.4%, 봉동 66.1%, 소양 54.1%, 효자 58.1%를 보여 주었다. 상 하류 유량검토를 통해서는 하리지점의 보 가물막이 공사 기간을 제외하고 전반적으로 적절한 상 하류 관계를 나타내었다. 본 연구는 대상유역의 유출특성을 분석하기 위한 것으로 강우자료의 산정은 전주지역의 기상청 자료를 이용하였으며, 평균강우량은 산술평균법에 의하였다.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.201-211
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• 2013

This study compares Customer Satisfaction Index(CSI) and the weight for each dimension by applying various methods of weight calculation and attempts to suggest some implications. For the purpose, the study classified the methods of weight calculation into the subjective method and the statistical method. Constant sum scale was used for the subjective method, and the statistical method was again segmented into correlation analysis, principal component analysis, factor analysis, structural equation model. The findings showed that there is difference between the weights from the subjective method and the statistical method. The order of the weights by the analysis methods were classified with similar patterns. Besides, the weight for each dimension by different methods of weight calculation showed considerable deviation and revealed the difference of discrimination and stability among the dimensions. Lastly, the CSI calculated by various methods of weight calculation showed to be the highest in structural equation model, followed by in the order of regression analysis, correlation analysis, arithmetic mean, principal component analysis, constant sum scale and factor analysis. The CSI calculated by each method showed to have statistically significant difference.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.1059-1065
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• 2008

Rainfall data is the most basic input data to analyze the hydrological phenomena and can be missing due to various reasons. In this research, a neural network based model to estimate missing rainfall data as approximate values was developed for 12 rainfall stations in the Soyang river basin to improve existing methods. This approach using neural network has shown to be useful in many applications to deal with complicated natural phenomena and displayed better results compared to the popular offline estimating methods, such as RDS(Reciprocal Distance Squared) method and AMM(Arithmetic Mean Method). Additionally, we proposed automated data reconciliation systems composed of a neural network learning processer to be capable of real-time reconciliation to transmit reliable hydrological data online.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.595-601
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• 2011

There is currently applied to the unit cost per a distance (KRW/km) for estimating the conceptual cost of civil work on basic planning stage of high speed railroad. This unit cost is an arithmetic average value based on historical data, which could be in big error. It also is difficult to explain the deficiency comparing the estimated cost derived from next basic design stage. This study provides the conceptual estimation model using by the parametric method and regression analysis. Independent variables are the distance and the geological materials (earth, weathered rock, soft-rock, hard-rock), extracting from the actual data to 36 contracts. The deviation between the unit costs estimated using the developed model and the actual cost data is presented in the range from -0.4% to +31%. This range is acceptable compared the typical range "-30% to + 50%". This model will improve the accuracy of existing method and be expected to contribute to effective total cost management and the economic aspects, reduce the financial expenditure.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.117-127
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• 1995

In this paper several methods for retriving appropriate values of effective soil moisture contents from natural soil surfaces are introduced and compared each other. The soil medium has usually a nonuniform moisture profile; i.e., relatively dry at the top layer and relatively wet at the bottom layer. The effective soil moisture represents the quantitative value of soil moisture of the inhomogeneous soil medium in an average sense. A simple method is an arithmetic averaging of soil moisture values obtained from several layers of a soil surface. Otherwise, the penetration depths can be computed from a homogeneous and an inhomogeneous soil surfaces and compared in order to obtain the effective soil mosture. The other method is to obtain the effective soil moisture by comparing the reflectivities from both of a homogeneous and an inhomogeneous surfaces. Those methods are compared and the reflectivity technique is examined in more detail since the rader scattering is dominated by the reflectivity instead of the penetration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.775-784
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• 2023

In terms of flood management, it is necessary to analyze quantitative rainfall and runoff from a spatial and temporal perspective and to analyze runoff for heavy rainfall events that are concentrated within a short period of time. The simulation and analysis results of rainfall-runoff models vary depending on the type and input data. In particular, rainfall data is an important factor, so calculating areal mean rainfall is very important. In this study, the areal mean rainfall of the Samcheok Osipcheon(Riv.) watersheds located in the mountainous terrain was calculated using the Arithmetic Mean Method, Thiessen's Weighting Method, and the Isohyetal Method, and the rainfall-runoff results were compared by applying the distributional model S-RAT and the lumped model HEC-HMS. The results of the temporal transferability study showed that the combination of the distributional model and the Isohyetal Method had the best statistical performance with MAE of 64.62 m³/s, RMSE of 82.47 m³/s, and R² and NSE of 0.9383 and 0.8547, respectively. It is considered that this study was properly analyzed because the peak flood volume occurrence time of the observed and simulated flows is within 1 hour. Therefore, the results of this study can be used for frequency analysis in the future, which can be used to improve the accuracy of simulating peak flood volume and peak flood occurrence time in mountainous watersheds with steep slopes.

• Information Systems Review
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• v.24 no.1
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• pp.39-57
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• 2022

This paper proposes the GMOPTBoost algorithm to improve the performance of the AdaBoost algorithm for bankruptcy prediction in which class imbalance problem is inherent. AdaBoost algorithm has the advantage of providing a robust learning opportunity for misclassified samples. However, there is a limitation in addressing class imbalance problem because the concept of arithmetic mean accuracy is embedded in AdaBoost algorithm. GMOPTBoost can optimize the geometric mean accuracy and effectively solve the category imbalance problem by applying Gaussian gradient descent. The samples are constructed according to the following two phases. First, five class imbalance datasets are constructed to verify the effect of the class imbalance problem on the performance of the prediction model and the performance improvement effect of GMOPTBoost. Second, class balanced data are constituted through data sampling techniques to verify the performance improvement effect of GMOPTBoost. The main results of 30 times of cross-validation analyzes are as follows. First, the class imbalance problem degrades the performance of ensembles. Second, GMOPTBoost contributes to performance improvements of AdaBoost ensembles trained on imbalanced datasets. Third, Data sampling techniques have a positive impact on performance improvement. Finally, GMOPTBoost contributes to significant performance improvement of AdaBoost ensembles trained on balanced datasets.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.2
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• pp.245-256
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• 2000

A moment-curvature relationship to simulate the behavior of reinforced concrete beam under cyclic loading is introduced. Unlike previous moment-curvature models and the layered section approach, the proposed model takes into consideration the bond-slip effect by using monotonic moment-curvature relationship constructed on the basis of the bond-slip relation and corresponding equilibrium equation at each nodal point. In addition, the use of curved unloading and reloading branches inferred from the stress-strain relation of steel gives more exact numerical result. The advantages of the proposed model, comparing to layered section approach, may be on the reduction in calculation time and memory space in case of its application to large structures. The modification of the moment-curvature relation to reflect the fixed-end rotation and pinching effect is also introduced. Finally, correlation studies between analytical results and experimental studies are conducted to establish the validity of the proposed model.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.3
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• pp.163-172
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• 1989

In order to study spatial variability of soil physical properties accross the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs), all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil particle size distribution analysis was made at 225 intersections of $15{\times}15$ grid with 10m interval. Field capacity, bulk density and saturated hydraulic conductivity were measured in situ at 594 intersections of $33{\times}18$ grid with 2.5m interval in only $6,000m^2$ reselected from $22,500m^2$ of sampling area for particle size distribution analysis. Sampled or measured soil depths were 0 to 10cm 25 to 35cm and 50 to 60cm at each intersections. The results are summarized as follows: 1. The coefficient of variance (CV) of various physical properties ranges from 4.8 to 128.8%. Saturated hydraulic conductivity is classified into the high variation group with CV greater than 100%, while the low variation group with CV smaller than 10% consists of bulk density. Other properties belong to the medium variation group with CV between 10 and 100%. 2. The appropriate number of soil samples for the determination of various physical properties with error smaller than 10% are calculated as one for bulk density, six for field moisture capacity, 16 for silt, 19 for clay, 69 for sand and 686 for saturated hydraulic conductivity. 3. Smooth frequency distribution and fractile diagram show that saturated hydraulic conductivity is in lognormal distribution while other physical properties are in normal distribution. 4. Serial correlation analysis reveals that the soil physical properties have spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of physical properties measured between the serial grid points in the direction of south to north following section boundary shows that the zone of influence showing stationarity ranges from 7.5 to 40m. In the direction of east to west across section boundary, the autocorrelogram of many physical properties shows peaks with the periodic interval of 30m, which are similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.225-231
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• 1991

In order to suggest the useful information on the fishing ground of the bigeye tuna Thunnus obesus(LOWE), a data base system was formed with catch data of the Korean tuna long liners during from 1975 to 1987 by using a set of 16 bits personal computer. This data base was constructed of the handling program and 4 types of data file processed from the monthly and yearly catch data of the whole tunas and the bigeye tuna. And when the system was started, the map of one among various Oceans such as the Pacific, the Atlantic and the Indian Ocean. is drawn on the monitor. And then the catch rates of the whole tunas or the catch ratios of bigeye tunas are indicated by the figured symbols and the colors on the sea divisions of 5$^{\circ}$ space of longitude and latitude respectively at the same time. Also this system has the preestimating program on the catch rates of the whole tunas and the bigeye tuna in the desired month and sea divisions. In the results than this data base system was handled and tested, very useful informations were obtained for the detection of tunas, especially bigeye tuna, and the preestimation was possible in a desired level.