• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.9-15
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• 2005

In the operation of distribution systems, DGs (Distributed Generations) are installed as an alternative to extension and the establishment of substations, transmission and distribution lines according to the increasing power demand. In the operation planning of DGs, determining optimal capacity and allocation achieves economical profitability and improves the reliability of power distribution systems. This paper proposes a determining method for the optimal number, size and allocation of DGs in order to minimize the operation costs of distribution systems. Capacity and allocation of DGs for economical operation planning duration are determined to minimize total cost composed with power buying cost, operation cost of DGs, loss cost and outage cost using the GA (Genetic Algorithm).

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.485-493
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• 2011

The proportional likelihood ratio order is an extension of the likelihood ratio order for the non-negative absolutely continuous random variables. In addition, the Lindley distribution has been over looked as a mixture of two exponential distributions due to the popularity of the exponential distribution. In this paper, we first recalled the above concepts and then obtained various properties of the Lindley distribution due to the proportional likelihood ratio order. These results are more general than the likelihood ratio ordering aspects related to this distribution. Finally, we discussed the proportional likelihood ratio ordering in view of the weighted version of the Lindley distribution.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.875-888
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• 2017

The Rayleigh distribution has been commonly used in life time testing studies of the probability of surviving until mission time. We focus on a reliability function of the Rayleigh distribution and deal with prior distribution on R(t). This paper is an effort to obtain Bayes estimators of rayleigh distribution with three different prior distribution on the reliability function; a noninformative prior, uniform prior and inverse gamma prior. We have found the Bayes estimator and predictive density function of a future observation y with each prior distribution. We compare the performance of the Bayes estimators under different sample size and in simulation study. We also derive the most plausible region, prediction intervals for a future observation.

• Genomics & Informatics
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• v.4 no.2
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• pp.65-70
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• 2006

Peptide mass mapping is the matching of experimentally generated peptides masses with the predicted masses of digested proteins contained in a database. To identify proteins by matching their constituent fragment masses to the theoretical peptide masses generated from a protein database, the peptide mass fingerprinting technique is used for the protein identification. Thus, it is important to know the theoretical mass distribution of the database. However, few researches have reported the peptide mass distribution of a database. We analyzed the peptide mass distribution of non-redundant protein sequence database in the NCBI after digestion with 15 different types of enzymes. In order to characterize the peptide mass distribution with different digestion enzymes, a power law distribution (Zipfs law) was applied to the distribution. After constructing simulated digestion of a protein database, rank-frequency plot of peptide fragments was applied to generalize a Zipfs law curve for all enzymes. As a result, our data appear to fit Zipfs law with statistically significant parameter values.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Wind and Structures
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• v.28 no.6
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• pp.369-380
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• 2019

Statistical distributions are very useful in describing wind speed characteristics and in predicting wind power potential of a specified region. Although the Weibull distribution is the most popular one in wind energy literature, it does not seem to be able to perfectly fit all the investigated wind speed data in nature. Thus, many studies are still being conducted to find flexible distribution for modelling wind speed data. In this study, we propose a new Odd-Burr Rayleigh distribution for wind speed characterization. The Odd-Burr Rayleigh distribution with two shape parameters is flexible enough to model different shapes of wind speed data and thus it can be an alternative wind speed distribution for the assessment of wind energy potential. Therefore, suitability of the Odd-Burr Rayleigh distribution is investigated on real wind speed data taken from different regions in the South Africa. Numerical results of the conducted analysis confirm that the new Odd-Burr Rayleigh distribution is suitable for modelling most of the considered real wind speed cases and it also can be used for predicting wind power.

• Communications of the Korean Mathematical Society
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• v.14 no.2
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• pp.353-364
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• 1999

We found the characterizations for convolution operators in the Beurling`s generalized distribution space to be hyperbolic.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.1-5
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• 2014

The plasma density distribution in between the electrode and lateral wall of a narrow gap CCP was investigated. The plasma density distribution was obtained using single Langmuir probe, having two peaks of density distribution at the center of electrode and at the peripheral area of electrodes. The plasma density distribution was compared with the RF fluctuation of plasma potential taken from capacitive probe. Ionization reactions obtained from numerical analysis using CFD-$ACE^+$ fluid model based code. The peaks in two region for plasma density and voltage fluctuation have similar spatial distribution according to input power. It was found that plasma density distribution between the electrode and the lateral wall is closely related with the local ionization.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.785-804
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• 2021

The proposal of new families has been worked out by many authors over recent years. Many ways to generate new families have been developed as the methods of addition, linear combination, composition and, one of the newer, the T-X family of distributions. Using this latter method, Korkmaz et al. (2018) proposed a new class called Weibull Marshall-Olkin-G (WMO-G) family. In the present work, we propose a new distribution, based on the WMO-G family, using the Lomax distribution as baseline, called Weibull Marshall-Olkin Lomax (WMOL) distribution. The hazard rate function of this distribution can be increasing, decreasing, bathtub-shaped, decreasing-increasing-decreasing and unimodal. Some properties of the proposed model are developed. Besides that, we consider method of maximum likelihood for estimating the unknown parameters of the WMOL distribution. We provide a simulation study in order to verify the asymptotic properties of the maximum likelihood estimates. The applicability of the new distribution to modeling real life data is proved by two real data sets.