• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.1-6
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• 2004

For a given plant design, improved decisions on when to shutdown an existing plant may be obtained by making better predictions of failure rates, by exerting efforts to collect more relevant information or by improving decision making models which put that information to best use. It is important that the models include the value of possible loss of lives and fear along with cleanup, decommissioning, relocation if the decisions derived from the model are to be useful. The decision model we have described enables us to investigate a class of optimal decisions on whether to shutdown or continue operating one period of time. The analysis and decision process is repeated at the end of each period with additional information about new costs and risks.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1678-1682
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• 2009

IRWMS(Integrated Real time Water Management System)은 우리나라의 수자원 운영환경에 부합하도록 하천유역에 수자원 통합관리 개념을 도입한 실시간 물관리 의사결정지원 시스템이다. 국내 기술로 개발하여 실무에 적용함으로써 수자원 이용 효율을 극대화하고 선진국 수준의 수자원 관리기술을 확보하기 위한 방안으로 개발되어졌다. 이러한 물관리 시스템 구축을 위해서는 통합 유역에 적합한 모형의 선택과 이수, 치수, 수질 관리 모델의 통합 방안, 해당 유역특성을 반영한 시스템 구성 방법, 각각의 모형의 입,출력 자료의 관리 및 실무에 적용하기 용이한 GUI 구성 등을 고려하여야 한다. 물관리 시스템은 GIS 기반의 해석모형과 웹기반의 정보, 지식 전달 시스템, 수문자료 관리를 위한 DB시스템 등으로 구성되어져 있으며 SOBEK, RIBASIM, MIKE BASIN, WEAP 등 다양한 물관리 시스템들은 각각의 개발 시기나 쓰임에 따라 해석모형과 DB의 사용유무 등 여러 기능들을 차별화하여 구성하고 있다. RIBASIM(RIver BAsin SIMulation)의 경우 다양한 해석모형 들을 각각의 과정에 따라 사용하고 있으며 CMT(Case Management tool), CAT(Case Analysis Tool)라 불리는 기능들을 통하여 각각의 과정을 순차적으로 진행하고 분석하고 있으며 자사의 수문DB관리 프로그램, 수질, GIS도구 등과 연동하여 사용되고 있다. MIKE BASIN의 경우 ArcGIS의 EXTENSION으로 강력한 GIS기능과 비쥬얼한 화면 구성을 그 특징으로 가지고 있다. IRWMS는 강우유출모형과 댐군 저수지 연계 운영모형, 수질모형으로 구성되어져 있으며 DB와의 연동을 통하여 실시간으로 의사결정자들이 의사결정을 지원하며 실무진 중심의 GUI구성을 통하여 실용성을 중심에 두었다. IRWMS는 금강, 낙동강의 구축사례에서 보듯이 실시간 운영으로 수자원 관리 실무진의 사용에 그 주안점을 두었지만 차후 범용화와 상기에서 언급한 여러 국내외 시스템들의 장점을 받아들인다면 각각의 유역특성에 맞는 다양한 활용으로 수자원기술의 선진화에 크게 기여를 할 것이다.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.951-970
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• 2015

The purpose of this study is to explore related variables to influence gifted college students' career conviction and to propose a structural model. For the study, 292 college students who have experienced university affiliated gifted education program during their school days. Rational decision making test, intrinsic motivation test, career decision efficacy test, and major conviction test were utilized. SPSS program and AMOS were used for statistical analyses. The results are summarized as follows. The fit of measurement model was found to be TLI=.923, CFI=.951, RMSEA=.077, indicating most of the fit indexes were acceptable. The path to career conviction from rational decision making and intrinsic motivation was found to be insignificant, suggesting a revised model. The fit of final revised measurement model was found to be TLI =.926, CFI=.951, RMSEA=.075, indicating the model was acceptable. Interestingly, the career decision efficacy was found to be the complete mediator among the rational decision making, intrinsic motivation, and career conviction. The results of the study showed that career decision efficacy has a very important role in gifted college students'career choice and decision. Implication of the study related to the career education and counseling has been discussed in depth.

• Agrochemical news magazine
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• v.23 no.5 s.178
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• pp.10-13
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• 2002

농약은 농산물 생산에 있어서 병해충 및 잡초를 방제함으로써 생산성을 높이는데 필수적인 농업자재로 인식하고 있다. 그런데 모든 화학물질이 그러하듯이 농약도 두 가지 양면성을 지니고 있다. 즉, 약효와 독성이다. 일반적으로 농약은 뿌려진 농약의 $0.1\%$이하만이 목표물이라고 할 수 있는 해충 및 잡초, 이병작물에 떨어지고 그 외는 비표적 생물 및 환경매체에 떨어짐으로써 생태계에 영향을 준다고 한다. 약효는 농약으로서 지녀야 하는 당연한 기능이지만 독성은 가능한 줄여야 할 기능이기 때문에 농약회사에서는 약효는 높으면서 사람과 생태계에는 좀 더 안전한 농약을 개발하기 위해 애쓰고 있다. 우리나라는 전세계적으로 볼 때 농약을 비교적 많이 사용하는 나라로 알려져 있으나 경제규모 및 사용량에 비해서 생태계에 대한 농약관리는 앞서가지 못하고 있는 것이 현실이다. 따라서 농약의 생태위해성 평가에 대한 기본적인 이해를 돕기 위해 이번호부터 연재를 통해 생태위해성에 대한 기본개념을 소개함과 동시에 국내외 농약등록제도에서의 생태위해성 의사결정 과정을 비교하고 마지막으로는 국내 농약관리제도에 있어서 생태독성분야의 의사결정에 대하여 개선방안을 제안하고자 한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.323-332
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• 2002

전자상거래와 같은 분산컴퓨팅환경에서는, 의사결정을 위해 협동적 문제해결과 사례기반의 자동 모형화가 더욱 중요시 되고 있다. 왜냐하면, 문제요구는 다양하고 이에 대응하기 위해 모든 모형을 준비한다는 것은 실제로 어려우며, 모형의 저장 및 관리관점에서도 비효율적이기 때문이다. 이에 따라, 최적화 에이전트 기반의 자동 모형화에 의한 문제해결을 위한 연구의 필요성이 인식되고 있다. 본 연구에서는 최적화 모형에 대한 지식이 부족한 사용자 수준의 XML 표현과 같은 문제요구를 이해하고, 최적화 모형 사례로부터 목표모형을 탐색하는 최적화 에이전트를 위한 사례기반 자동 모형화의 프레임웍을 제시한다. 이를 위해, 자동 모형화 지식의 표현과 목표모형 탐색을 위한 전방향 추론절차를 제시한다 최적화 에이전트는 모형화 노력을 줄이기 위해서, 민감도분석을 통해 성능이 평가된 탐색 알고리즘을 사용한다.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.725-735
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• 2008

Due to recent climate change, flood damages have been increased, but it is difficult to construct large hydraulic structure for flood control such as dam because of environmental, economical and political problems. For this reason, several researches and studies have tried to use washland as an alternative of hydraulic facility. Because sizes of washlands are usually smaller than those of dams or reservoirs, there can be many available locations for washlands in a basin and proper combination of these locations can reduce flood disasters efficiently. However, in case there are many available locations for washland and many combinations to consider, it is very difficult to determine the optimal combination which yields to provide the maximum benefit. For the more, hydraulic approach that used in previous studies to calculate flood reduction effect needs a lot of time for calculation and sometimes can not give the final result. In this study, the flood reduction effect of washland is calculated by hydrologic approach and decision making model for optimal location of washland using genetic algorithm for determination of optimal solution is developed. The developed model has been applied to the Ansung River basin in order to examine the applicability and the application result shows that developed model can be used as decision making model for washland.

• Korean Business Review
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• v.22 no.1
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• pp.139-156
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• 2009

This article investigates the relationships between motivation and revisit intention of visitors to Gangneung Danoje Festival as cultural festival with social demand. Out of 550 questionnaires distributed, a total of 514 usable questionnaires were collected. The hypothesized causal model was tested by logit model, which included satisfaction model to each program as well as overall satisfaction model to cultural festival. Model 1 is constructed with satisfaction and revisit intention to each program, and Model 2 with overall satisfaction and revisit intention to cultural festival. In this models causal variables were inputted including satisfaction to festival programs, frequency of visitation, days of stay, time required to destination. In Model 1 positive sign were shown by causal variables as satisfaction to each program, frequency of visitation, days of stay but negative signs was shown by time required to festival place. In Model 2 sign directions of causal variables were same in Model 1. In comparison, Model 2 is more significant than Model 1 on the basis of statistical theory as significance level and coefficient of determination. Consequently, cultural festival managers should test the satisfaction level of visitors to each program of cultural festival and make efforts to establish advanced program in order to attract more visitors.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• ETRI Journal
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• v.5 no.3
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• pp.3-8
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• 1983

In the area of computer network planning, a location-allocation-size problem is involved. Since multi-facility location-allocation-size problems are very complex in formulating a mathematical model, it is a usual practise to adopt alternative approaches, which give no optimal results, instead of the optimal solution by mathematical approach. In this article, however, an attempt is made to formulate a mathematical model for the decision making problem of computer network design.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.51-69
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• 2002

In the supply chain environment on the web, collaborative problem solving and case-based modeling has been getting more important, because it is difficult to cope with diverse problem requirements and inefficient to manage many models as well. Hence, the approach on case-based modeling is required. This paper provides a framework that generates a goal model based on multiple cases, modeling knowledge, and forward chaining and it also develops a search algorithm through sensitivity analysis to reduce the modeling effort.