• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.827-837
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• 2012

The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.147-175
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• 2006

This paper attempts to incorporate three important factors-perceptions, behavior and valuation-in analysing consumers' responses to health risks from environmental pollutants. Using a survey sample of 500 consumers in the Chonbuk province area, this paper empirically investigated determinants of risk perceptions from using tap water as drinking water. Most consumers were considerably concerned about health risks from drinking tap water. Moreover, those subjective concerns were not random, but were systematically related to individuals' demographic variables such as age, gender, and family size. Those subjective beliefs also influenced respondents' purchase intentions on safer water bottles, in response to a contingent behavior question of presenting two types of water bottles. The technical risk information provided in the survey had significant effects on purchase intentions only when it was interacted with respondents' actual averting practice. In addition, the sample selection effects were present by eliminating respondents who decided not to purchase either of two types of water bottles. The potential selection bias had impacts on the coefficients of the price difference variable, and subsequently the estimates of the price increments for health risk reductions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.46-55
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• 2012

This study proposes an estimate method of willingness to pay(WTP) for real-time route guidance systems using contingent valuation method(CVM) under double bounded dichotomous choice question(DBDCQ) and analysis for impact factors of WTP estimation. This study assumed that provided real-time traffic information service is optimal route concepts dealing with traffic conditions on origin-destination. Analysis targets were classified into two groups as short distance path and middle distance path for estimating WTP for realtime route guidance system in a year using the survival analysis method and the regression model with personal information, actual condition and satisfaction of information usage and users' awareness and usage of facilities. As a result, mean WTP of realtime route guidance system is 4,034won/year in short distance path, and 4,884won/year in middle distance path. Therefore real-time route guidance system for longer distance path is recognized as more valuable than shorter distance path. Moreover, the necessity of information was required on a higher income group and higher WTP was estimated on owners of vehicle group and lower awareness of a route group.

• Journal of Environmental Policy
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• v.14 no.2
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• pp.49-72
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• 2015

Forests in the upstream contributed to improve the quality of water resources for the residents downstream. However, upon structural examination of how the Han River Watershed Management Fund was spent, it became apparent that the fund was not spent toward forest management in the upstream. An additional budget must be allocated if the Watershed Management Committee is to contribute to the management of the upstream forests with such awareness. Therefore, the aim of the study was to assess the willingness to pay and to calculate of budget for forest management in the upstream for water quality improvement. Three hundred surveys on watershed beneficiaries were conducted using biased sampling method. The result was analyzed with conditional logit model and mixed logit model. Forest management, a target variable, was found to have statistical significance. Based on this result, the size of the expected budget was estimated to be minimum 20,526 million won to maximum 20,928 million won.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.109-116
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• 2004

Petroleum reservoir characterization is a process for quantitatively describing various reservoir properties in spatial variability using all the available field data. Porosity and permeability are the two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. In un-cored intervals and well of heterogeneous formation, porosity and permeability estimation from conventional well logs has a difficult and complex problem to solve by conventional statistical methods. This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear regression method to develop transformation between the selected well logs and core analysis data. The intelligent technique is demonstrated with an application to the well data in offshore Korea. The results show that this technique can make more accurate and reliable properties estimation compared with previously used methods. The intelligent technique can be utilized a powerful tool for reservoir characterization from well logs in oil and natural gas development projects.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.346-351
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• 2021

With the goal of eradicating overwork, overload, and speeding of general freight cars(cargo) by the Ministry of Land, Infrastructure and Transport, Infrastructure and Transport, the "The Fare of safe transportation for freight cars System" has been enforced since 2020. 'The Fare of safe transportation for freight cars' rate for each item is being applied and supplemented, but the 'The Cost of safe transportation for freight cars' of general freight cars (cargo) and steel items is under discussion. The purpose of this study was to estimate the willingness to pay( WTP) for cargo. A survey was conducted on shippers, transportation companies (arrangers, carriers), and cargo drivers (using direct questioning among contingent valuation method (CVM) and the Tobit Regression analysis was conducted, and the average and median values of freight rates were derived using the estimated results, and the willingness to pay by tonnage of freight cars was confirmed. It is expected that the results of this study can be used as a reference to the "The Fare of safe transportation for freight cars Committee" an organization for deliberation and resolution of the 'The Cost of safe transportation for freight cars'.

• International Area Studies Review
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• v.15 no.3
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• pp.239-261
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• 2011

The cyclicality of productivity has been one of the essential issues in macroeconomics. Since Solow(1957) developed the dominant approach to the measurement of productivity growth, Solow's approach, which assumes the perfect competition, the constant returns to scale, and the full use of input factor has been modified particularly in Hall's(1990) and Basu's(1996) works. Their researches take account of market power, returns to scale, and variable factor utilization. This paper establishes the empirical model based on Hall's(1990) and Basu's(1996) models, estimates 4 types of Solow's reidual in manufacturing and 2 service industries over the period 1975:1-2010:4, and analyzes the cyclicality of measured productivity. The result proved the measured productivity to be procyclical in manufacturing industries and electricity and water industry, and in contrast to the Basu's, the variable factor utilization transformed the countercyclicality of measured productivity into its procyclicality in the Korean economy.

• Journal of the Korean Geotechnical Society
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• v.23 no.11
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• pp.87-98
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• 2007

For the quick rehabilitation of a fire-damaged tunnel structure, it is the most important procedure to investigate the fire-induced damaged zone rapidly. This study aims to propose a new drilling resistance testing method by which mechanical properties of tunnel concrete lining altered by high temperature can be estimated easily and continuously. Especially, it alms to derive the relationships to estimate mechanical properties of mortar and concrete materials from drilling parameters. To obtain the optimum testing condition, a series of drilling resistance tests were carried out for mortar specimens. When the rotation per minute of drill bit, tile penetration rate and the bit diameter were 1,300 rpm, 1.40 mm/sec, and 10 mm respectively, the deviation of measured drilling resistance forces was minimal. Under the optimum testing condition, the relationships between drilling resistance and mechanical properties of mortar specimens were shown to be very favorable. The concept of replacing a mean value of resistance farces measured during drilling with the resistance energy was proposed to consider the effects of randomly distributed aggregates inside a concrete material on drilling resistance. When the concept was applied to concrete materials, a favorable relationship between actual compressive strength and drilling resistance energy was also successfully derived.

• Journal of the Korea Concrete Institute
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• v.14 no.4
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• pp.457-466
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• 2002

An artificial neural network was applied to predict compressive strength, slump value and mix proportion of a concrete. Standard mixed tables were trained and estimated, and the results were compared with those of the experiments. To consider variabilities of material properties, the standard mixed fables from two companies of Ready Mixed Concrete were used. And they were trained with the neural network. In this paper, standard back propagation network was used. The mix proportion factors such as water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate and air entraining admixture were used. For the arrangement on the approval of prediction of mix proportion factor, the standard compressive strength of $180kgf/cm^2{\sim}300kgf/cm^2$, and target slump value of 8 cm, 15 cm were used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of $210kgf/cm^2{\sim}240kgf/cm^2$, and target slump value of 12 cm and 15 cm wore used because these ranges are most frequently used. In results, in the prediction of mix proportion factor, for all of the water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate, air entraining admixture, the predicted values and the values of standard mixed tables were almost the same within the target error of 0.10 and 0.05, regardless of two companies. And in the prediction of compressive strength and slump value, the predicted values were converged well to the values of standard mixed fables within the target error of 0.10, 0.05, 0.001. Finally artificial neural network is successfully applied to the prediction of concrete mixture and compressive strength.

• Survey Research
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• v.9 no.2
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• pp.1-27
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• 2008

Problems of incomplete data are pervasive in statistical analysis. In particular, incomplete data have been an important challenge in repeated measures studies. The objective of this study is to give a brief introduction to missing data mechanisms and conventional/recent missing data methods and to assess the performance of various missing data methods under ignorable and non-ignorable missingness mechanisms. Given the inadequate attention to longitudinal studies with missing data, this study applied recent advances in missing data methods to repeated measures models and investigated the performance of various missing data methods, such as FIML (Full Information Maximum Likelihood Estimation) and MICE(Multivariate Imputation by Chained Equations), under MCAR, MAR, and MNAR mechanisms. Overall, the results showed that listwise deletion and mean imputation performed poorly compared to other recommended missing data procedures. The better performance of EM, FIML, and MICE was more noticeable under MAR compared to MCAR. With the non-ignorable missing data, this study showed that missing data methods did not perform well. In particular, this problem was noticeable in slope-related estimates. Therefore, this study suggests that if missing data are suspected to be non-ignorable, developmental research may underestimate true rates of change over the life course. This study also suggests that bias from non-ignorable missing data can be substantially reduced by considering rich information from variables related to missingness.