• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.2
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• pp.59-68
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• 1998

This study was conducted to derive optimal design floods by generalized gamma distribution model of the annual maximum series at eight watersheds along Geum, Yeongsan and Seomjin river systems. Design floods obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model were compared by the relative mean errors and graphical fit along with 95% confidence limits plotted on gamma probability paper. The results were analyzed and summarized as follows. 1. Basic statistics and parameters were calculated by the generalized gamma distribution model using different methods for parameters. 2. Design floods according to the return periods were obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model. 3. It was found that design floods derived by sundry averages method for parameters and Cunnane method for plotting position in the generalized gamma distribution are much closer to those of the observed data in comparison with those obtained by the other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4. Reliability of design floods derived by sundry averages method in the generalized gamma distribution was acknowledged within 95% confidence interval.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.3
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• pp.83-95
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• 1997

This study was conducted to derive optimal design floods by Gamma distribution models of the annual maximum series at eight watersheds along Geum , Yeong San and Seom Jin river Systems, Design floods obtained by different methods for evaluation of parameters and for plotting positions in the Gamma distribution models were compared by the relative mean errors and graphical fit along with 95% confidence interval plotted on Gamma probability paper. The results were analyzed and summarized as follows. 1.Adequacy for the analysis of flood flow data used in this study was confirmed by the tests of Independence, Homogeneity and detection of Outliers. 2.Basic statistics and parameters were calculated by Gamma distribution models using Methods of Moments and Maximum Likelihood. 3.It was found that design floods derived by the method of maximum likelihood and Hazen plotting position formular of two parameter Gamma distribution are much closer to those of the observed data in comparison with those obtained by other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4.Reliability of derived design floods by both maximum likelihood and method of moments with two parameter Gamma distribution was acknowledged within 95% confidence interval.

• Water for future
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• v.13 no.4
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• pp.41-50
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• 1980

The prupose of this study are the theoretical examination of Gamma distribution function and its application to hydraulic engineering, that is studying the simulation of monthly streamflow by the Gamma distribtution function model(Gamma Model) based on Monte Carlo technique. In the analysis, monthly streamflow data in the Nak Dong River, the Han River, and the Keum River were used and the data were changed to modular coefficient in order to make the analysis convenient. At first, the fitness of monthly streamflow to 2-Parameter Gamma distribution was tested by Chi-square and Kolmogrov-Smironov test, by which it was found the monthly streamflow were fit well to this Gamma distribution function. Then, the Gamma Model based on the Gamma distribution and Monte Carlo Method was used in the simulation of monthly streamflow, and simulateddata showed that all their stastical characteristics were preserved well in the simulation. Consequently, it can be concluded that the Gamma Model is suitable for the simulation of monthly streamflow series directly by using the Mote Carlo technique.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.93-109
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• 2007

Gamma distributions are some of the most popular models for hydrological processes. In this paper, a very flexible family which contains the gamma distribution as a particular case is introduced. Evidence of flexibility is shown by examining the shape of its pdf and the associated hazard rate function. A comprehensive treatment of the mathematical properties is provided by deriving expressions for the nth moment, moment generating function, characteristic function, Renyi entropy and the asymptotic distribution of the extreme order statistics. Estimation and simulation issues are also considered. Finally, a detailed application to drought data from the State of Nebraska is illustrated.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.753-758
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• 2004

A generalization of gamma distribution is defined by slightly modifying the form of Kobayashi's generalized gamma function(1991). We define a new extended gamma distribution and study some properties of this distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.97-103
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• 2006

Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs. And most of industrial processes are known to follow the non-normal distribution. Therefore, the control chart is required to be developed for monitoring the processes with non-normal short production runs by the CV characteristics for a non-normal distribution. In this paper, we suggest the control chart for monitoring the processes with a gamma short runs by the CV characteristics for a gamma distribution. This control chart is denoted by the gamma CV control chart. Futhermore evaluated the performance of the gamma CV control chart by average run length(ARL).

• Journal of Environmental Impact Assessment
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• v.23 no.4
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• pp.285-295
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• 2014

In this study, we analyzed probability distribution of EMCs (Event Mean Concentration) of COD, TOC, T-N, T-P and SS from rice paddy fields and compared the mean values of observed EMCs and the median values of estimated EMCs ($EMC_{50}$) through probability distribution. The field monitoring was conducted during a period of four crop-years (from May 1, 2008, to September 30. 2011) in a rice cultivation area located in Emda-myun, Hampyeong gun, Jeollanam-do, Korea. Four probability distributions such as Normal, Log-normal, Gamma, and Weibull distribution were used to fit values of EMCs from rice paddy fields. Our results showed that the applicable probability distributions were Normal, Log-normal, and Gamma distribution for COD, and Normal, Log- Normal, Gamma and Weibull distribution for T-N, and Log-normal, Gamma and Weibull distribution for T-P and TOC, and Log-normal and Gamma distribution for SS. Log-normal and Gamma distributions were acceptable for EMCs of all water quality constituents(COD, TOC, T-N, T-P and SS). Meanwhile, mean value of observed COD was similar to median value estimated by the gamma distribution, and TOC, T-N, T-P, and SS were similar to median value estimated by log-normal distribution, respectively.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.221-230
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• 2007

The exponential and the gamma distributions have been the traditional models for drought duration and drought intensity data, respectively. However, it is often assumed that the drought duration and drought intensity are independent, which is not true in practice. In this paper, an application of the bivariate gamma exponential distribution is provided to drought data from Nebraska. The exact distributions of R=X+Y, P=XY and W=X/(X+Y) and the corresponding moment properties are derived when X and Y follow this bivariate distribution.

• International Journal of Reliability and Applications
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• v.16 no.2
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• pp.81-98
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• 2015

The Exponentiated Gamma (EG) distribution is one of the important families of distributions in lifetime tests. In this paper, a new generalized version of this distribution which is called kumaraswamy Exponentiated Gamma (KEG) distribution is introduced. A new distribution is more flexible and has some interesting properties. A comprehensive mathematical treatment of the KEG distribution is provided. We derive the $r^{th}$ moment and moment generating function of this distribution. Moreover, we discuss the maximum likelihood estimation of the distribution parameters. Finally, an application to real data sets is illustrated.

• Fire Science and Engineering
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• v.30 no.2
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• pp.62-67
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• 2016

In this study, the optical depth is analyzed with the effects of droplet size distribution of the water curtain nozzle to attenuate the radiative heat transfer. The HELOS/VARIO equipment is used for the measurement of the droplet size distributions. The spray characteristics are quantified by the investigation of Deirmenjian's modified gamma distribution function. The distribution constant of the nozzle can be obtained as ${\alpha}=1$ and ${\gamma}=5.2$. The generalized equation of the optical depth related with the droplet size distribution is introduced. These results will be applicable to the analysis of the design condition of the water curtain nozzle.