• Title/Summary/Keyword: 설계가중치

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A Study on the Effect of Preliminary Feasibility Study System Improvement (예비타당성조사 제도 개선 효과에 관한 연구)

  • Park, Seung Jun
    • Smart Media Journal
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    • v.11 no.7
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    • pp.70-75
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    • 2022
  • In 2019, the government improved the system to reduce the maximum weight of economic feasibility items in the comprehensive evaluation from 50% to 45% in order to improve the problem that economic feasibility is a decisive factor in passing the preliminary feasibility study. This study is to analyze the effect of system improvement in 2019 and verified the difference between before and after system improvement. As a result of regression analysis and correlation analysis, both periods showed high correlation, and the difference through Z-test was analyzed as not statistically significant. This result means that institutional improvement to reduce the impact of economics was not effective. Therefore, it is judged that it is necessary to discuss the design of a more effective comprehensive evaluation study through research such as reevaluating the weights of each item in the comprehensive evaluation in various ways in existing projects.

A Design of HPPS(Hybrid Preference Prediction System) for Customer-Tailored Service (고객 맞춤 서비스를 위한 HPPS(Hybrid Preference Prediction System) 설계)

  • Jeong, Eun-Hee;Lee, Byung-Kwan
    • Journal of Korea Multimedia Society
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    • v.14 no.11
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    • pp.1467-1477
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    • 2011
  • This paper proposes a HPPS(Hybrid Preference Prediction System) design using the analysis of user profile and of the similarity among users precisely to predict the preference for custom-tailored service. Contrary to the existing NBCFA(Neighborhood Based Collaborative Filtering Algorithm), this paper is designed using these following rules. First, if there is no neighbor's commodity rating value in a preference prediction formula, this formula uses the rating average value for a commodity. Second, this formula reflects the weighting value through the analysis of a user's characteristics. Finally, when the nearest neighbor is selected, we consider the similarity, the commodity rating, and the rating frequency. Therefore, the first and second preference prediction formula made HPPS improve the precision by 97.24%, and the nearest neighbor selection method made HPPS improve the precision by 75%, compared with the existing NBCFA.

Development of Weather Information System for Water Resources Management of Guem River (금강유역 수자원 운영을 위한 기상정보제공시스템 구축)

  • Jeong, Chang-Sam;Hwang, Man-Ha;Ko, Ick-Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.1007-1012
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    • 2008
  • 유역통합수자원관리의 시작은 기상예측정보의 제공으로부터 시작된다. 하지만, 기상예측정보는 단기, 중기, 장기로 구분되며, 제공되는 정보가 수자원 운영에 필요한 정보와 시간적으로나 공간적으로 차이가 나며, 가공에 많은 전문가들의 노력이 필요하여 실무에서의 적용에 많은 어려움이 따른다. 따라서 본 연구에서는 이러한 문제들을 해결하고 용이하게 수자원 운영자에게 필요한 기상정보를 적절한 형태의 가공을 통하여 자동적으로 제공해 주는데 그 목적이 있다. 이러한 시스템의 구축을 통해 향후 수자원 운영에 있어 필수적인 의사결정 정보를 제공해 주어 수자원의 이용효율을 높이고자 한다. 구축된 시스템은 금강 유역에 대해 소유역단위로 장기 유출의 입력자료인 일단위 예측 강수를 30일간 제공하도록 시스템을 구축하였다. 단기(1일$\sim$2일)에는 RDAPS의 모의 결과인 Grib파일을 자동 추출하여 예측 강수를 제공한다. 1일에 두 번 모의되는 RDAPS의 결과를 일단위로 제공하기 위해 여러 가지 case별 분석을 실시하여 가장 적합한 기법을 이용하여 일단위 시계열을 구축하는 시스템을 설계하였다. 중기(3일$\sim$10일)에는 GDAPS 결과인 Grib파일을 자동 추출하여 유역단위 시계열을 구축한 뒤 과거 자료를 이용한 연 평균 자료를 이용하여 가중치를 곱하여 시계열을 구축하였다. 장기(11일$\sim$30일) 시계열의 구축을 위해서는 단기 및 중기 예측 시계열을 이용하여 과거 시계열 자료와의 통계적 비교 분석을 이용하여 유사 시계열을 추출한 후 과거 자료에 대한 평균값과 기상 전망을 이용하여 가중치를 부여하는 방법 등을 이용하여 시스템을 구축하였다. 본 시스템은 한국수자원공사에서 운영 중인 RRFS모형의 입력 자료를 자동 생성할 수 있는 기능을 제공하도록 설계되었다. 이러한 시스템의 구축을 통해 기상정보를 다루는데 익숙하지 않은 수자원 운영자들에게 비교적 용이하게 유역단위 기상예측 정보를 추출하는데 큰 도움이 될 것으로 기대한다.

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Visually Weighted Group-Sparsity Recovery for Compressed Sensing of Color Images with Edge-Preserving Filter (컬러 영상의 압축 센싱을 위한 경계보존 필터 및 시각적 가중치 적용 기반 그룹-희소성 복원)

  • Nguyen, Viet Anh;Trinh, Chien Van;Park, Younghyeon;Jeon, Byeungwoo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.9
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    • pp.106-113
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    • 2015
  • This paper integrates human visual system (HVS) characteristics into compressed sensing recovery of color images. The proposed visual weighting of each color channel in group-sparsity minimization not only pursues sparsity level of image but also reflects HVS characteristics well. Additionally, an edge-preserving filter is embedded in the scheme to remove noise while preserving edges of image so that quality of reconstructed image is further enhanced. Experimental results show that the average PSNR of the proposed method is 0.56 ~ 4dB higher than that of the state-of-the art group-sparsity minimization method. These results prove the excellence of the proposed method in both terms of objective and subjective qualities.

An Extended Faceted Classification Scheme and Hybrid Retrieval Model to Support Software Reuse (소프트웨어 재사용을 지원하는 확장된 패싯 분류 방식과 혼합형 검색 모델)

  • Gang, Mun-Seol;Kim, Byeong-Gi
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.1
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    • pp.23-37
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    • 1994
  • In this paper, we design and implement the prototype system, and propose the Extended Faceted Classification. Scheme and the Hybrid Retrieval Method that support classifying the software components, storing in library, and efficient retrieval according to user's request. In order to designs the classification scheme, we identify several necessary items by analyzing basic classes of software components that are to be classified. Then, we classify the items by their characteristics, decide the facets, and compose the component descriptors. According to their basic characteristics, we store software components in the library by clustering their application domains and are assign weights to the facets and its items to describe the component characteristics. In order to retrieve the software components, we use the retrieval-by-query model, and the weights and similarity for easy retrieval of similar software components. As the result of applying proposed classification scheme and retrieval model, we can easily identify similar components and the process of classification become simple. Also, the construction of queries becomes simple, the control of the size and order of the components to be retrieved possible, and the retrieval effectiveness is improved.

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Optimization of Mobile Robot Predictive Controllers Under General Constraints (일반제한조건의 이동로봇예측제어기 최적화)

  • Park, Jin-Hyun;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.4
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    • pp.602-610
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    • 2018
  • The model predictive control is an effective method to optimize the current control input that predicts the current control state and the future error using the predictive model of the control system when the reference trajectory is known. Since the control input can not have a physically infinitely large value, a predictive controller design with constraints should be considered. In addition, the reference model $A_r$ and the weight matrices Q, R that determine the control performance of the predictive controller are not optimized as arbitrarily designated should be considered in the controller design. In this study, we construct a predictive controller of a mobile robot by transforming it into a quadratic programming problem with constraints, The control performance of the mobile robot can be improved by optimizing the control parameters of the predictive controller that determines the control performance of the mobile robot using genetic algorithm. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.

Ensemble Design of Machine Learning Technigues: Experimental Verification by Prediction of Drifter Trajectory (앙상블을 이용한 기계학습 기법의 설계: 뜰개 이동경로 예측을 통한 실험적 검증)

  • Lee, Chan-Jae;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.3
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    • pp.57-67
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    • 2018
  • The ensemble is a unified approach used for getting better performance by using multiple algorithms in machine learning. In this paper, we introduce boosting and bagging, which have been widely used in ensemble techniques, and design a method using support vector regression, radial basis function network, Gaussian process, and multilayer perceptron. In addition, our experiment was performed by adding a recurrent neural network and MOHID numerical model. The drifter data used for our experimental verification consist of 683 observations in seven regions. The performance of our ensemble technique is verified by comparison with four algorithms each. As verification, mean absolute error was adapted. The presented methods are based on ensemble models using bagging, boosting, and machine learning. The error rate was calculated by assigning the equal weight value and different weight value to each unit model in ensemble. The ensemble model using machine learning showed 61.7% improvement compared to the average of four machine learning technique.

Understanding Complex Design Features via Design Effect Models (설계효과모형을 통한 설계요소의 유용성 이해)

  • Park, Inho
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1217-1225
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    • 2015
  • Survey research, data is commonly collected through a sample design with complex design features that allow the relative efficiency on the precision of an estimator to be measured using the concept of the design effect compared to simple random sampling as a reference design. This concept is most useful when the design effect can be expressed as a function of various design features. We propose a design effect formula suitable under a stratified multistage sampling by generalizing Gabler et al. (1999, 2006)'s approaches for multistage sampling. Its use can either guide improvement in the design efficiency when in design stage or enable the evaluation of the adopted design features afterwards.

Selection of the economically optimal parameters in the EWMA control chart (지수가중이동평균관리도의 경제적 최적모수의 선정)

  • 박창순;원태연
    • The Korean Journal of Applied Statistics
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    • v.9 no.1
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    • pp.91-109
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    • 1996
  • Exponentially weighted moving averae(EWMA) control chart has been used widely for process monitoring and process adjustment recently, but there has not been many studies about the selection of the parameters. Design of the control chart can be classified into the statistical design and the economic design. The purpose of the economic design is to minimize the cost function in which all the possible costs occurring during the process are probability given the Type I error probability. In this paper the optimal parameters of the EWMA chart are selected for the economic design as well as for the statistical design. The optimal parameters for the economic design show significantly different from those of the statistical design, and especially the weight is always larger than that used in the statistical design. In the economic design, we divide the model into the single assignable cause model and the multiple assignable causes model caacording to number of which is used as the average context of the multiple assignable causes, it shows that the selection of the parameters may be misleading when the multiple assignable causes exist in practice.

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Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight (효율과 무게를 고려한 원심압축기 최적설계에 관한 연구)

  • Lee, Younghwan;Ha, Kyung Gu;Kang, Shin-Hyoung
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.39 no.4
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    • pp.293-299
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    • 2015
  • Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.