• 산업경영시스템학회지
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• 제45권4호
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• pp.127-133
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• 2022

Many manufacturers applying third party logistics (3PLs) have some challenges to increase their logistics efficiency. This study introduces an effort to estimate the weight of the delivery trucks provided by 3PL providers, which allows the manufacturer to package and load products in trailers in advance to reduce delivery time. The accuracy of the weigh estimation is more important due to the total weight regulation. This study uses not only the data from the company but also many general prediction variables such as weather, oil prices and population of destinations. In addition, operational statistics variables are developed to indicate the availabilities of the trucks in a specific weight category for each 3PL provider. The prediction model using XGBoost regressor and permutation feature importance method provides highly acceptable performance with MAPE of 2.785% and shows the effectiveness of the developed operational statistics variables.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.697-708
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• 2008

본 논문은 금융기관에서 활용하고 있는 운영리스크 측정모형에 대한 적합성검증 방법 중 안정성 검증에 관한 것이다. 신용리스크와는 달리 운영리스크는 손실자료의 특징, 과거 자료의 부족 그리고 적합성검증을 위한 이론적 도구의 부족 등으로 인해 현재 적절한 적합성검증 방안에 제시되지 못하고 있다. 본 논문에서는 운영리스크 VaR(Value at Risk) 추정값의 안정성을 평가하는 적합성검증 방법을 제시하고 이를 활용한 실증분석을 통해 제안된 방법에 대한 실제적 활용 가능성을 확인해 보고자 한다. 구체적으로 본 논문에서는 붓스트랩 방법을 활용하여 운영리스크 VaR의 신뢰구간을 생성함으로써 운영리스크 VaR 추정값의 안정성을 검증하는 기법을 제안하였으며, 이를 토대로 적합에 따른 운영리스크 VaR 추정값의 안정성을 측정하는 방안도 제시하였다.

• International Journal of Reliability and Applications
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• 제5권2호
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• pp.75-80
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• 2004

Relationships between inventory policy and operational availability of military equipment maintained under a logistics support system are analyzed. A continuous review inventory model with a stochastic demand typically used in a military logistics support is considered and some numerical studies are provided.

• 산업경영시스템학회지
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• 제38권3호
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• pp.87-94
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• 2015

Recently, management based on statistical data has become a big issue and the importance of the statistics has been emphasized for the management innovation in the defense area. However, the Military Management based on the statistics is hard to expect because of the shortage of the statistics in the military. There are many military information systems having great many data created in real time. Since the infrastructure for gathering data form the many systems and making statistics by using gathered data is not equipped, the usage of the statistics is poor in the military. The Analytical Defense Statistics System is designed to improve effectively the defense management in this study. The new system having the sub-systems of Data Management, Analysis and Service can gather the operational data from interlocked other Defense Operational Systems and produce Defense Statistics by using the gathered data beside providing statistics services. Additionally, the special function for the user oriented statistics production is added to make new statistics by handling many statistics and data. The Data Warehouse is considered to manage the data and Online Analytical Processing tool is used to enhance the efficiency of the data handling. The main functions of the R, which is a well-known analysis program, are considered for the statistical analysis. The Quality Management Technique is applied to find the fault from the data of the regular and irregular type. The new Statistics System will be the essence of the new technology like as Data Warehouse, Business Intelligence, Data Standardization and Statistics Analysis and will be helpful to improve the efficiency of the Military Management.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.211-215
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• 2003

Network security should be first considered in a distributed computing environment with frequent information interchange through internet. Clear classification is needed for information users should protect and for information open outside. Basically proper encrypted database system should be constructed for information security, and security policy should be planned for each site. This paper describes access control, user authentication, and User Security and Encryption technology for the construction of database security system from network users. We propose model of network encrypted database security system for combining these elements through the analysis of operational and technological elements. Systematic combination of operational and technological elements with proposed model can construct encrypted database security system secured from unauthorized users in distributed computing environment.

• Journal of Nutrition and Health
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• 제26권3호
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• pp.357-366
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• 1993

The purposes of this study were to investigate the operational affecting productivity in hospital foodservice, and to examine the relationships between operational factors affecting productivity. The 28 hospitals over 400 beds in Seoul were mailed questionnaires assessing the factors that affect productivity in hospital foodservice(23 hospitals responded). Data analyses included descriptive statistics. Pearson product moment correlation analysis, and stepwise multiple regression analysis. The result of Pearson product moment correlation analysis indicated that the percentage of patient meals was significantly correlated to the productivity (r=.5560, p<.01). Stepwise multiple regression analysis indicated that the percentage of patient meals and the average work hours of employees were significant predictors of the operational factors at productivity.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1204-1209
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• 1990

This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.

• 응용통계연구
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• 제26권1호
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• pp.49-58
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• 2013

자료포락분석(data envelopment analysis)은 여러 종류의 투입요소와 산출요소를 이용하여 의사결정단위(decision making unit)들 간의 상대적 효율성을 평가하기 위해 많이 사용되는 기법이다. 본 연구에서는 자료포락분석을 이용하여 지방대학들의 연구 및 교육분야에 대한 효율성을 분석한다. 먼저, 우리나라 국 공립 대학들의 효율성에 대해 살펴보고, 지역거점대학(regional flagship national universities)과 비거점(non-flagship)대학 간의 효율성이 통계적으로 유의한지 여부를 탐색한다.

• Industrial Engineering and Management Systems
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• 제12권1호
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• pp.16-22
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• 2013

This paper proposes a new concept of comonotonicity of uncertain vector based on the uncertainty theory. In order to understand the comonotonicity of uncertain vector, some equivalent definitions are presented. Following the proposed concept, some basic properties of comonotonic uncertain vector are investigated. In addition, the operational law is given for calculating the uncertainty distributions of monotone functions of comonotonic uncertain variables. With the help of operational law, the comonotonic uncertain vector is applied to the premium pricing problems. At last, some numerical examples are given to illustrate the application.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.