• Title/Summary/Keyword: Loss distribution

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Estimation of the parameter in an Exponential Distribution using a LINEX Loss

  • Woo, Jung-Soo;Lee, Hwa-Jung;Eun, Kab-Sook
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.1-10
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    • 2002
  • A Bayes estimator of the scale parameter in an exponential distribution will be considered by a LINEX error, then the risk of the Bayes estimator using a LINEX loss will be compared with that of a Bayes estimator using a square error.

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BMAP/M/N/O Queueing System in Random Environments

  • Kim, Che-Soong
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2007.04a
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    • pp.461-465
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    • 2007
  • The BMAP/M/N/O queueing system operating in Markovian random environment is investigated. The stationary distribution of the system is calculated. Loss probability and other performance measures are calculated. Numerical experiments which show the necessity of taking into account the influence of random environment and correlation in input flow are presented.

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Batch Size Distribution in Input Flow to Queues with Finite Buffer

  • Kim, Che-Soong;Kim, Ji-Seung
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • 2005.11a
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    • pp.271-275
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    • 2005
  • Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.

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Optimal Var allocation in System planning by Stochastic Linear Programming(II) (확률선형 계획법에 의한 최적 Var 배분 계뵉에 관한 연구(II))

  • Song, Kil-Yeong;Lee, Hee-Yoeng
    • Proceedings of the KIEE Conference
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    • 1989.11a
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    • pp.191-193
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    • 1989
  • This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.

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A Method to Allocate Real Power Losses of Transmission Lines using Loss Distribution factors (손실배분계수를 이용한 송전선로 유효전력 손실의 배분법)

  • Ro, Kyoung-Soo
    • Proceedings of the KIEE Conference
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    • 1999.07c
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    • pp.1259-1261
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    • 1999
  • The paper proposes a simple method to calculate the portion of real power losses allocated to individual loads. The method is implemented by loss distribution factors, and analyses the share of loads in transmission line losses. Effectiveness of the algorithm is verified by a computer simulation. The results can be used to compute the cost of ancillary services under deregulated environment in electric power industries.

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Analysis of BMAP/M/N/0 Queueing System for Telecommunication Network Traffic Control (통신망 트래픽 제어를 위한 BMAP/M/N/0 대기행렬모형 분석)

  • Lee, Seok-Jun;Kim, Che-Soong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.30 no.4
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    • pp.39-45
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    • 2007
  • The BMAP/M/N/0 queueing system operating in Markovian random environment is investigated. The stationary distribution of the system is derived. Loss probability and other performance measures of the system also are calculated. Numerical experiments which show the necessity of taking into account the influence of random environment and correlation in input flow are presented.

Estimation of the exponentiated half-logistic distribution based on multiply Type-I hybrid censoring

  • Jeon, Young Eun;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.47-64
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    • 2020
  • In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

Distribution Feeder Reconfiguration Using Heuristic Rules (경험적 규칙을 이용한 배전계통의 재구성기법)

  • Cho, Si-Hyung;Choi, Byoung-Youn;Woo, Kwang-Bang
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.363-365
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    • 1991
  • This paper presents a method for feeder reconfiguration in order to operate distribution systems efficiently using heuristic rules. The reconfiguration method presented here not only eliminates various abnormal states but also achieves minimum power loss and optimum load balance of the distribution feeders under normal operating condition transfering loads from one feeder to anoter applying the experiences of the experts. To implement the method effectively, a best-first tree searching strategy based on heuristics is used to evaluate the various load transfer alternatives. The development of a rule-based system aimed at the reduction of the search space is presented as a means of implementing the best-first searching strategy. The results of the computer simulation of the above procedure are as follows; 1) achieving minimum power loss of the distribution feeder adopting the optimum load transfer alternative. 2) Enhencing system reliability and achieving load balance through rational allocation of the feeder loads.

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Application of Genetic Algorithm for Loss Minimization in Distribution Systems (배전계통에서 손실 최소화를 위한 유전자 알고리즘의 적용)

  • Jeon, Young-Jae;Kim, Hoon;Lee, Seung-Youn;Son, Hag-Sig;Park, Soung-Ok;Kim, Jae-Chul
    • Proceedings of the KIEE Conference
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    • 2000.07a
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    • pp.156-158
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    • 2000
  • This paper presents a efficient algorithm for loss reduction of distribution system by automatic sectionalizing switch operation in distribution systems of radial type. To apply genetic algorithm to reconfiguration of distribution system, in this paper we propose the string type and efficient reconfiguration procedure. We also discuss the more elaborate search techniques of solution space as well as the simple genetic algorithm. The experimental results show that the proposed genetic algorithm have the ability to search a good solution.

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Fuzzy-GA Application for Allocation and Operation of Dispersed Generation Systems in Composite Distribution Systems (복합배전계통에서 분산형전원의 설치 및 운영을 위한 Fuzzy-GA 응용)

  • 김규호;이유정;이상봉;유석구
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.10
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    • pp.584-592
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    • 2003
  • This paper presents a fuzzy-GA method for the allocation and operation of dispersed generator systems(DGs) based on load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The problem formulation considers an objective to reduce power loss of distribution systems and the constraints such as the number or total capacity of DGs and the deviation of the bus voltage. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 12 bus and 33 bus test systems to demonstrate its effectiveness. .