• 제목/요약/키워드: integrated weighting

검색결과 51건 처리시간 0.023초

Energy Efficiency Classification of Agricultural Tractors in Korea

  • Shin, Chang-Seop;Kim, Kyeong-Uk;Kim, Kwan-Woo
    • Journal of Biosystems Engineering
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    • 제37권4호
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    • pp.215-224
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    • 2012
  • Purpose: This study was conducted to classify the energy efficiency of 131 tractor models tested during from 2006 to 2010 in Korea. Methods: Four sub-indexes were developed using the fuel consumptions at 60% and 90% of rated speed with partial loads and at pull speeds of 3.0 km/h and 7.5 km/h with maximum drawbar pull. Weighting factors of the sub-indexes were also considered to reflect the characteristics of tractor's actual working hours in Korea. Four sub-indexes were integrated into a classification index. Using the developed classification index, a five-classification system was made on the basis of normal distribution of tractors over the classification range. Percentage of $1^{st}$ grade interval was expected to be close to 15%, $2^{nd}$ grade 20%, $3^{rd}$ grade 30%, $4^{th}$ grade 20%, $5^{th}$ grade 15%. Results: Number of $1^{st}$ grade was 21, $2^{nd}$ grade 23, $3^{rd}$ grade 39, $4^{th}$ grade 33, $5^{th}$ grade 15 among 131 models. Conclusions: Classification index was developed by integrating four sub-indexes. By the classification method using developed index, distribution of classified tractors was acceptable for practical application.

개선된 데이터마이닝을 위한 혼합 학습구조의 제시 (Hybrid Learning Architectures for Advanced Data Mining:An Application to Binary Classification for Fraud Management)

  • Kim, Steven H.;Shin, Sung-Woo
    • 정보기술응용연구
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    • 제1권
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    • pp.173-211
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    • 1999
  • The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

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Study on Multimedia Expert Diagnostic System of Chicken Diseases

  • Lu Changhua;Wang Lifang;Nong, Hu-Yi;Wang Qiming;Lu Qingwen
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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    • pp.508-510
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    • 2001
  • Adopting the method of user weighting fuzzy mathematics, the author accomplished the subject title “Study on Expert System of Chicken\`s Common Diseases Diagnostics”, which could properly diagnose 30 kinds of chicken\`s common diseases and the accordance rate reached 80% verified through 244 disease cases. On the basis of the accomplishment, the multimedia technology was adopted further more to establish a system, which integrated with the input, display, query, and processing of sound, picture and text etc., combined with the previous chicken disease diagnostic expert system, make the output information of computer more rich and comprehensive, and the accordance rate of disease diagnosis could be improved. The system consists of database, knowledge base, graphics and picture base. This system is easy to operate and interface of which is vivid and intuitive. It could output diagnostic result and prescribe rapidly, so that, such a system is not only adapted to large, medium chicken farm but also to grass-roots veterinary station for developing health care and disease diagnosing. It is sure that the system could have side prospect of application.

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EXPLORING THE FUEL ECONOMY POTENTIAL OF ISG HYBRID ELECTRIC VEHICLES THROUGH DYNAMIC PROGRAMMING

  • Ao, G.Q.;Qiang, J.X.;Zhong, H.;Yang, L.;Zhuo, B.
    • International Journal of Automotive Technology
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    • 제8권6호
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    • pp.781-790
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    • 2007
  • Hybrid electric vehicles(HEV) combined with more than one power sources have great potential to improve fuel economy and reduce pollutant emissions. The Integrated Starter Generator(ISG) HEV researched in this paper is a two energy sources vehicle, with a conventional internal combustion engine(ICE) and an energy storage system(batteries). In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming(DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. A fuel-economy-only case and a fuel & emissions case can be achieved by changing specific weighting factors. The simulation results of the fuel-economy-only case show that there is a 45.1% fuel saving potential for this ISG HEV compared to a conventional transit bus. The test results present a 39.6% improvement in fuel economy which validates the simulation results. Compared to the fuel-economy-only case, the fuel & emissions case further reduces the pollutant emissions at a cost of 3.2% and 4.5% of fuel consumption with respect to the simulation and test result respectively.

우리나라 광역시 도시압축성 평가에 관한 연구 (A Study on the Urban Compactness Evaluation of Korean Metropolises)

  • 이일희;이주형
    • 한국산학기술학회논문지
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    • 제13권7호
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    • pp.3224-3231
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    • 2012
  • 통합적이고 객관화된 도시압축성 평가방법에 대한 연구가 필요하다. 이를 위하여 압축도시(compact city)와 관련된 문헌 등 선행연구를 통하여 도시압축성 평가요소를 추출하였다. 이렇게 설정된 평가요소는 전문가조사를 통한 객관화 과정과 AHP계층구조모형을 통하여 평가요소별로 가중치를 결정한다. 이러한 평가분석의 틀을 토대로 우리나라 6대 광역시의 도시압축성을 평가하고 표준점수(z-score)화하여 상대적인 차이를 분석하고자 하였다. 이러한 분석결과는 압축도시에 대한 정책 결정에 필요한 기본 자료로서 구도심의 도시재생 등 압축도시계획에 활용될 수 있을 것이다.

An Integrated Approach to Measuring Supply Chain Performance

  • Theeranuphattana, Adisak;Tang, John C.S.;Khang, Do Ba
    • Industrial Engineering and Management Systems
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    • 제11권1호
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    • pp.54-69
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    • 2012
  • Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

지리정보시스템(GIS)과 다기준 분석법(MCA)을 적용한 연안지역 평가 (An Assessment of Coastal Area Using Geographic Information Systems and Multi-Criteria Analysis)

  • 최희정;박정재;황철수
    • 한국지역지리학회지
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    • 제13권2호
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    • pp.143-155
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    • 2007
  • 다양한 이해집단과 목적들이 상충하는 연안지역에 대해 공간정책을 결정하기 위해서는 물리적 자연조건, 사회 경제적 조건, 그리고 의사결정과정에서의 가치체계가 통합적으로 반영될 수 있어야 하고, 선호도가 반영된 요소를 효율적으로 분석할 수 있는 체계가 갖추어져야 한다. 본 연구에서는 지리정보시스템이라는 공통의 플랫폼에 다양한 유형의 연안지역 공간정보를 변환 통합하고, 다기준 분석법의 하나인 AHP를 이용해 의사결정에 영향을 미치는 기준들 사이에 가중치를 설정하여, 가중치를 적용한 개별 레이어를 지도대수와 중첩분석을 통해 최종 결과 레이어를 생성하였다. 이와 같이 지리정보시스템의 공간분석 기능을 다기준 분석법과 동적으로 통합함으로써 새롭게 변화된 정보들을 편리하게 분석과정에 포함시키거나 분석 결과가 단순하고 명확하게 설명되어 궁극적으로 정책결정자에게 유용한 정보를 제공할 수 있는 장점을 확인하였다. 특히 평가항목에 대한 가중치 할당 방식은 다양한 관전에 따른 정책결정과정을 모의할 수 있어 기존의 연구에 비해 유연성을 갖는다.

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수학과 중등임용 확률과 통계학 기출문항 분석 (An Analysis on the Past Items of Probability and statistics in Secondary School Mathematics Teacher Certification Examination)

  • 김창일;전영주
    • 한국학교수학회논문집
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    • 제20권4호
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    • pp.387-404
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    • 2017
  • 본 연구에서는 최근 4개년(2014~2017학년도)의 수학교과내용학 기출문항 가운데 확률과 통계학 문항을 분석 대상 문항으로 분류하고, 수학과 임용시험 문항 분석틀을 기반으로 분류된 문항을 분석하였다. 그 결과 첫째, 확률과 통계학 교육과정의 정상화를 유도하기 위하여 4개 평가영역이 고르게 출제되어야 한다. 둘째, 통합적 사고, 종합 분석적인 사고 평가가 이루어져야 한다. 셋째, 수학적 사고력과 논리적 역량을 측정할 수 있는 문항 발문이 사용되어야 한다. 넷째, 문항 수에 의한 출제 비율은 7.7%~10.0%이고, 배점에 따른 비율은 이 보다 낮은 5.0%~7.5% 사이로 출제되었다. 다섯째, 적정난이도 안정화 정책을 유지하고 있다. 여섯째, 확률과 통계학은 귀납적 관점의 문제해결력 측정을 해야 한다는 결론과 시사점을 얻었다.

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Nonlinear stochastic optimal control strategy of hysteretic structures

  • Li, Jie;Peng, Yong-Bo;Chen, Jian-Bing
    • Structural Engineering and Mechanics
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    • 제38권1호
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    • pp.39-63
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    • 2011
  • Referring to the formulation of physical stochastic optimal control of structures and the scheme of optimal polynomial control, a nonlinear stochastic optimal control strategy is developed for a class of structural systems with hysteretic behaviors in the present paper. This control strategy provides an amenable approach to the classical stochastic optimal control strategies, bypasses the dilemma involved in It$\hat{o}$-type stochastic differential equations and is applicable to the dynamical systems driven by practical non-stationary and non-white random excitations, such as earthquake ground motions, strong winds and sea waves. The newly developed generalized optimal control policy is integrated in the nonlinear stochastic optimal control scheme so as to logically distribute the controllers and design their parameters associated with control gains. For illustrative purposes, the stochastic optimal controls of two base-excited multi-degree-of-freedom structural systems with hysteretic behavior in Clough bilinear model and Bouc-Wen differential model, respectively, are investigated. Numerical results reveal that a linear control with the 1st-order controller suffices even for the hysteretic structural systems when a control criterion in exceedance probability performance function for designing the weighting matrices is employed. This is practically meaningful due to the nonlinear controllers which may be associated with dynamical instabilities being saved. It is also noted that using the generalized optimal control policy, the maximum control effectiveness with the few number of control devices can be achieved, allowing for a desirable structural performance. It is remarked, meanwhile, that the response process and energy-dissipation behavior of the hysteretic structures are controlled to a certain extent.

정규화된 탄성파 파동장 자료의 향상된 전파형 역산 (Improved full-waveform inversion of normalised seismic wavefield data)

  • 김희준
    • 지구물리와물리탐사
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    • 제9권1호
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    • pp.86-92
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    • 2006
  • 정규화된 파동장을 이용하는 탄성파 전파형 역산법은 기존의 전파형 역산법에서 필요로 하는 탄성파원 예측으로 인해 야기되는 잠재적인 역산오차를 피할 수 있다. 본 논문에서는 이러한 전파형 역산법에 가중 평활화제약을 추가하여 분해능을 높였으며, 모든 주파수성분을 동시에 역산하지 않고 주파수 별로 순차적으로 역산하도록 수정하였다. 새로운 방법은 간단한 2 차원 단층모델에 적용하여 검증하였다. 가장 큰 개선점은 적분감도에 기초하여 결정한 가중계수를 모델변수에 도입한 점이다. 모델변수에 가중계수를 적용하면 평활화제약을 선택적으로 완화할 수 있기 때문에 영상화 재구성 시 잘못된 영상을 줄이는데 효과적이다. 다중 단일주파수 역산은 다중주파수 동시역산을 대치할 수 있으며, 특히 작은 주파수부터 먼저 사용하는 순차적인 단일주파수 역산은 계산효율면에서 유용하다.