• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.755-758
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• 2008

Currently, the increased run-off and the shortened arrival time are one of the causes of the city environmental disasters in urbanization. Therefore, it is necessary to properly design the hydrologic structures, but it is very difficult to forecast the values necessary to design from the planning stage. Moreover, as the parameter is changed due to the urban development, it is difficult not only to analyze the run-off influences but also to find the related studies and literatures. The purpose of this study is to utilize the results as the important basic data of the hydrologic structures, its proper design and run-off influences through the sensibility analysis of the model parameter variables. In this study, the absolute and relative sensibility analysis method were used to find out the correlation through the sensibility analysis of the topology and hydrology parameters. Especially, in this study, the changes in the run-off amount and volume were calculated according to increase/decrease in CN, the coefficient of discharge, and the empirical formula is prepared and proposed through the regressive analysis among the parameters. In the meantime, the parameter sensibility analysis was performed through the simulation HEC-HMS that is used and available in Korea. From the results of this study, it was found that the run-off amount is increased about by 10% when the CN value is increased by 5% before and after the development through the HEC-HMS simulation and data analysis. As long as there will be additional data collection analysis and result verification, and continuous further studies to find out the parameters proper to the domestic circumstances, it is expected to considerably contribute to the proper design of the hydrologic structures with respect to the ungauged basin.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.211-226
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• 2017

The chain-ladder method, for which run-off data is employed is popularly used in the rate-adjustment and loss-reserving practices of non-life-insurance and health-insurance companies. The method is applicable when the underlying assumption of a consistent development pattern is in regards to a cumulative loss payment after the occurrence of an insurance event. In this study, a modified chain-ladder algorithm is proposed for when the assumption is considered to be only partially appropriate for the given run-off data. The concept of a structural-change point in the run-off data and its reflection in the estimation of unpaid loss amounts are discussed with numerical illustrations. Experience data from private health insurance coverage in Korea were analyzed based on the suggested method. The performance in estimation of loss reserve was also compared with traditional approaches. We present evidence in this paper that shows that a reflection of a structural-change point in the chain-ladder method can improve the risk management of the relevant insurance products. The suggested method is expected to be utilized easily in actuarial practice as the algorithm is straightforward.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.551-562
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• 2008

The loss reserve is defined as a provision for an insurer's liability for claims or an insurer's estimate of the amount an individual claim will ultimately cost. For the estimation of the loss reserve, the data which make up the claims in general is represented as run-off triangle. The chain ladder method has known as the most representative one in the estimation of loss reserves based on such run-off triangular data. However, this fails to capture change point in trend. In order to test of structural changes of development factors, we will present the test statistics and procedures. A real data analysis will also be provided.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.701-707
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• 1999

This study was initiated to collect background pollutant data for rural watersheds. The effluent/run-off polutant load and run-off ratio of the study areas were calculated and the two types of regression equations, L=a$.$Q+b and L=c$.$Qd where L and Q are the pollutant load(L) and discharge (Q), were derived. We acquired that the correlation coeffcients of the two types of regression equations were over than 90% except for BOD . Therefore, L-Q equations would be a measure to predict water quality of rural watersheds.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.4
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• pp.52-65
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• 1984

In general precise estimation of hourly of daily distribution of the long-term run-off should be very important in a design of source of irrigation. However, there have not been a satisfying method for forecasting of stationar'y long-term run-off in Korea. Solving this problem, this study introduces unit-hydrograph method frequently used in short-term run-off analysis into the long-term run-off analysis, of which model basin was selected to be Sumgin-river catchment area. In the estimation of effective rainfall, conventional method neglects the Soil moisture condition of catchment area, but in this study, the initial discharge (qb) occurred just before rising phase of the hydrograph was selected as the index of a basin soil moisture condition and then introduced as 3rd variable in the analysis of the reationship between cumulative rainfall and cumulative loss of rainfall, which built a new type of separation method of effective rainfall. In next step, in order to normalize significant potential error included in hydrological data, especially in vast catchment area, Snyder's correlation method was applied. A key to solution in this study is multiple correlation method or multiple regressional analysis, which is primarily based on the method of least squres and which is solved by the form of systems of linear equations. And for verification of the change of characteristics of unit hydrograph according to the variation of a various kind of hydrological charateristics (for example, precipitation, tree cover, soil condition, etc),seasonal unit hydrograph models of dry season(autumn, winter), semi-dry season (spring), rainy season (summer) were made respectively. The results obtained in this study were summarized as follows; 1.During the test period of 1966-1971, effective rainfall was estimated for the total 114 run-off hydrograph. From this estimation results, relative error of estimation to the ovservation value was 6%, -which is mush smaller than 12% of the error of conventional method. 2.During the test period, daily distribution of long-term run-off discharge was estimated by the unit hydrograph model. From this estimation results, relative error of estimation by the application of standard unit hydrograph model was 12%. When estimating by each seasonal unit bydrograph model, the relative error was 14% during dry season 10% during semi-dry season and 7% during rainy season, which is much smaller than 37% of conventional method. Summing up the analysis results obtained above, it is convinced that qb-index method of this study for the estimation of effective rainfall be preciser than any other method developed before. Because even recently no method has been developed for the estimation of daily distribution of long-term run-off dicharge, therefore estimation value by unit hydrograph model was only compared with that due to kaziyama method which estimates monthly run-off discharge. However this method due to this study turns out to have high accuracy. If specially mentioned from the results of this study, there is no need to use each seasonal unit hydrograph model separately except the case of semi-dry season. The author hopes to analyze the latter case in future sudies.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.411-423
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• 2009

In the current paper, by extending Verall (1990)'s work, we propose a new Bayesian model for analyzing run-off triangle data. While Verall's (1990) work only account for the calendar year and evolvement time effects, our model further accounts for the "absolute time" effects. We also suggest a Markov Chain Monte Carlo method that can be used for estimating the proposed model. We apply our proposed method to analyzing three empirical examples. The results demonstrate that our method significantly reduces prediction error when compared with the existing methods.

• The Journal of Fisheries Business Administration
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• v.33 no.2
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• pp.49-74
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• 2002

This study examines, from an economic perspective, the reasons for introducing a resource taxe system into the Korean off-shore fisheries and the type of charges that can be introduced. Following a review of the charging systems in other advanced fisheries, we consider the types of charging scheme and some implications for the Korean off-shore fishing industry. Charges could be used for recovering part of fisheries management cost from the industry(i.e. administration, enforcement, research, etc). This can be justified on the grounds that the fishing industry is the main beneficiary of management and that it should therefore bear at least part of the cost involved. It is arguable that publicly-funded management is in effect a subsidy to the industry. Using charges to raise revenue in excess of the cost of management would represent the extraction of a public rent from the fishery resource, but the short-run financial consqquences for the industry would be significant. Results from a qualtitative analysis suggest that while any new charge will have a significant financial impact on the industry in the short run, a landings tax would have a lesser impact on fleet structure in the long run. The study also considers the possibility of a capital gains tax on license sales in order to recover some rent from the industry. Despite any short run-financial consequences, making the fishing industry pay for at least some of the cost of management could benefit the industry as a whole if there were more cooperation between industry and managers as a result. It is acknowledged, however, that there could be disputes over the relative management costs of different sectors of the industry. Even though this study makes few specific recommendations about charging the Korean off-shore fishing industry, it does advise that the issue be reviewed on the basis of the entire Korea fisheries. Finally, the study notes that insufficient data are available on the economic performance of the Korean off-shore fishing vessels and it recommands that a comprehensive system for the collection of costs and earnings data be put in place. It also suggests that MOMAF pay much attention to the permit right market and its transactions.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.343-357
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• 2014

In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.

• Magazine of the Korean Society of Agricultural Engineers
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• v.20 no.3
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• pp.4724-4731
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• 1978

Using hydrometric data from an upland river in North Wales, a relationship between rate of river flow and water stored within the catchment area (catchment storage) is assumed to exist, and is evaluated from an analysis of winter recession curves. This storage/river flow relationship, when combined with water balance equations, produces a set of equations which may be used for "routing" input of rainfall through a storage with defined outflow characteristics, providing a straightforward method of flood prediction and analysis from rainfall data. Recorded and predicted flood hydrographs are compared, and the effectiveness and limitations of the method are considered. The development of a complete mathematical model, embodying the storage/river flow relationship, and suitable for generation of continuous run-off records from rainfall and evaporation data, is also considered.