• 한국수자원학회논문집
• /
• 제56권4호
• /
• pp.273-284
• /
• 2023

최근 지속적인 가뭄으로 물 공급에 큰 어려움을 겪고 있으며, 이러한 극한 사상의 발생은 기후변화에 따라 더욱 빈번해질 것으로 전망된다. 본 연구는 기후변화에 따른 댐 운영 가뭄 취약성을 평가하고자, 보다 넓은 범위에서 미래 기후변화의 변동성을 반영할 수 있는 decision scaling 기법을 제안하였다. 충청남도 보령댐을 시범유역으로 선정하고 양적 신뢰도를 이용하여 평가한 결과, 보령댐의 가뭄 취약도는 도수로 반영 여부에 따라 95.80% 에서 98.13%까지 변동하였고, 기후변화에 매우 취약한 것으로 나타났다. 더불어 유전 알고리즘 기반 최적의 헤징룰을 산정하여 가뭄 취약성의 저감 효과를 분석하였고, 다양한 사회·경제적 변화에 대응하기 위해 세 가지 수요 시나리오(고수요, 저수요, 기준수요) 하에서 평가를 진행하였다. 양적 신뢰도와 극한가뭄 발생 빈도를 평가 기준으로 분석한 결과, 두 헤징룰은 K-water의 용수공급 조정기준 대비 저수요 시나리오에서 공급 안정도를 개선시킴으로써 극한가뭄에 적절히 대처할 수 있는 방법으로 사용될 수 있을 것이다.

• 방사성폐기물학회지
• /
• 제18권4호
• /
• pp.517-536
• /
• 2020

The radionuclide inventory in radioactive waste from nuclear power plants should be determined to secure the safety of final repositories. As an alternative to time-consuming, labor-intensive, and destructive radiochemical analysis, the indirect scaling factor (SF) method has been used to determine the concentrations of difficult-to-measure radionuclides. Despite its long history, the original SF methodology remains almost unchanged and now needs to be improved for advanced SF implementation. Intense public attention and interest have been strongly directed to the reliability of the procedures and data regarding repository safety since the first operation of the low- and intermediate-level radioactive waste disposal facility in Gyeongju, Korea. In this review, statistical methodologies for SF implementation are described and evaluated to achieve reasonable and advanced decision-making. The first part of this review begins with an overview of the current status of the scaling factor method and global experiences, including some specific statistical issues associated with SF implementation. In addition, this review aims to extend the applicability of SF to the characterization of large quantities of waste from the decommissioning of nuclear facilities.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.192-194
• /
• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.

• 한국의류학회지
• /
• 제26권1호
• /
• pp.83-94
• /
• 2002

This study was intended to identify fabric impact on decision-making process for clothing purchase, to determine evaluation factors of clothing, and to analyze consumer's preference for fabric on clothing purchase. 396 questionnaires distributed to college students were analyzed by descriptive statistics, oneway ANOVA, correlation, factor analysis and multidimensional scaling. The results are as follows; (1) Fabric impacted on the pre-purchase evaluation and the post-purchase process. (2) 4 factors - physical properties, outer-consciousness, self-satisfaction, and appropriateness- were determined as evaluation factors. Though fabric was included in the physical properties, fabric presented high correlations with other evaluative elements. (3) The most preferred fabric was being composed of natural fiber in fiber contents and having softness in sensation. As a result of multidimensional scaling, 2 dimensions of fabric sensation were developed as 'soft-hard'and 'thin-thick'.

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 1997년도 추계학술발표회논문집(1)
• /
• pp.475-480
• /
• 1997

In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making fur both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors.

• 한국통신학회논문지
• /
• 제40권3호
• /
• pp.419-424
• /
• 2015

판정의거(decision-directed: DD) 등화는 수신 신호의 눈모형이 완전히 닫힌 채널 조건에서는 눈모형을 충분히 열지 못하여 블라인드 등화기를 초기화하는 데는 효과적이지 않은 것으로 알려져 있다. 본 논문에서는 기존 DD 알고리즘의 오차를 대체하는 새로운 오차를 제안한다. 새로운 DD 오차는 신호점 판정의 모듈러스를 기존 DD 오차에 스케일링한 것으로, 이를 적용한 새로운 DD 알고리즘은 기존 DD와는 달리 등화 초기의 닫힌 눈모형을 여는데 효과적이다. 새로운 오차를 적용한 DD 알고리즘은 블라인드 초기화에 널리 쓰이는 CMA에 비해 우수한 수렴 특성을 보이며, 특히 다중 모듈러스를 가지는 신호 등화에 유용하다. 고차 QAM 신호에 대한 모의실험을 통해 새로운 DD 알고리즘의 성능을 검증하였다.

• 환경영향평가
• /
• 제9권4호
• /
• pp.363-372
• /
• 2000

For any particular development project or environmental regulations, decision-making criteria is required and conflicts among criteria should be resolved. It is necessary to investigate criteria that government agencies employ in making decisions that influence the environment. The evaluation of alternative development proposals and regulatory measures involves much more than environmental issues. Economic, technical, and social factors should be considered along with environmental impacts when making evaluations. Evaluation should be based on values of all individuals who may be affected by public or private decisions. There are many evaluation methods for determining how individuals and groups value alternative public actions. Numerous weighting-scaling methodologies can be used in such evaluations. These methodologies represent adaptations of multiple-criteria or multiple-attribute decision-making techniques. Environmental risk assessment which accounts for uncertainties in choosing among alternative policies and projects is increasingly used.

• 한국수자원학회논문집
• /
• 제44권7호
• /
• pp.565-576
• /
• 2011

본 연구에서는 대상유역 내에 설치가 가능한 지역이 다수 존재하는 강변저류지의 설치 우선순위를 결정하기 위한 방안을 제시하였다. 강변저류지의 최적위치 선정을 위해 기존의 수행된 연구들은 각각의 장단점이 있으나, 의사결정을 위해 사용되는 변수의 통합과정에서 발생하는 오류는 해결해야할 가장 큰 문제이다. 특히 의사결정을 위해 고려해야할 다양한 변수를 하나의 기준으로 통합하기 위한 자료가 불충분한 국내의 경우, 의사결정을 위해 사용되는 가정들을 최소화하며, 다양한 변수들은 모두 고려할 수 있는 방안이 필요하게 된다. 본 연구에서는 제안된 기법은 강변저류지 최적위치 선정을 위해 수행된 기존 연구결과들의 장점을 포함하며, 보다 많은 변수들을 고려할 수 있도록 개발되었다. 기존에 제안된 방법을 이용하여 단위저류용량대비 홍수저감효과에 의한 우선순위, 상대적 중요도를 고려한 우선순위, 경제성평가에 의한 우선순위 및 공간계획적합성 평가에 의한 우선순위를 선정하고, 이들 네 가지 순위와 다차원척도법을 이용하여 최종적인 하나의 순위를 도출한다. 제안된 기법을 안성천유역의 13개 후보강변저류지를 대상으로 적용하였으며, 기존의 연구결과와 비교하였다.

• International Journal of Contents
• /
• 제13권2호
• /
• pp.29-34
• /
• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• 한국기계가공학회지
• /
• 제11권2호
• /
• pp.125-136
• /
• 2012

Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.