• 대한기계학회논문집A
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• 제26권10호
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• pp.2060-2066
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• 2002

The closed-loop state and input observer is a pole-placement type observer and estimates unknown state and input variables simultaneously. Pole-placement type observers may have poor transient performance with respect to ill-conditioning factors such as unknown initial estimates, round-off error, etc. For the robust transient performance, the effects of these ill-conditioning factors must be minimized in designing observers. In this paper, the transient performance of the closed-loop state and input observer is investigated quantitatively by considering the error bounds due to ill-conditioning factors. The performance indices are selected from these error bounds and are related to the observer robustness with respect to the ill -conditioning factors. The closed-loop state and input observer with small performance indices is considered as a well-conditioned observer from the transient perspective.

• Asia pacific journal of information systems
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• 제7권1호
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• pp.67-83
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• 1997

The utility of learning techniques in investment analysis has been demonstrated in many areas, ranging from forecasting individual stocks to entire market indexes. To date, however, the application of artificial intelligence to financial forecasting has focused largely on short predictive horizons. Usually the forecast window is a single period ahead; if the input data involve daily observations, the forecast is for one day ahead; if monthly observations, then a month ahead; and so on. Thus far little work has been conducted on the efficacy of long-term prediction involving multiperiod forecasting. This paper examines the impact of alternative procedures for extended prediction using knowledge discovery techniques. One dimension in the study involves temporal granularity: a single jump from the present period to the end of the forecast window versus a web of short-term forecasts involving a sequence of single-period predictions. Another parameter relates to the numerosity of input variables: a technical approach involving only lagged observations of the target variable versus a fundamental approach involving multiple variables. The dual possibilities along each of the granularity and numerosity dimensions entail a total of 4 models. These models are first evaluated using neural networks, then compared against a multi-input jump model using case based reasoning. The computational models are examined in the context of forecasting the S&P 500 index.

• Spatial Information Research
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• 제20권6호
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• pp.69-76
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• 2012

본 연구에서는 산업연관분석을 통해 공간정보산업의 특징을 도출하였다. 이를 위하여 공간정보산업을 재분류하고 이에 맞게 산업연관표를 수정하여 공간정보산업을 분석하였으며 생산유발계수, 영향력계수, 감응력계수를 도출하였다. 그 결과 공간정보산업은 생산유발효과는 작으나 전방연쇄효과가 매우 큰 산업으로 확인되었다. 이를 기반으로 공간정보산업 육성을 위한 정책의 방향성을 '산업생태계 조성, 고도화와 활용도 향상 병행, 장기적 관점 수립'으로 제시하였다.

• 동력기계공학회지
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• 제3권4호
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• pp.69-78
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• 1999

In the single-input and single-output system, the parameter of plant is scalar polynomial, but in the multiple input and multiple output, it accompanies, being matrix polynomial, the consideration of observable controlability index or problems non-commutation in matrix polynomial as well as degree, and it is more complex to deal with. Therefore, it is thought that a full research on the single-input and single-output system is not sufficient. This paper proposes that problems of minimum variance self-tuning regulator by using numerical calculation example of multivariable system and pole assignment self-tuning regulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.322-326
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• 1989

This paper describes design procedure of suboptimal control to minimize a performance index which is represented as sum of square output error and the heat input power in arc welding process. Heat input and temperature of a fixed point on the surface of the material are concerned as input and output of the process, repectively. The suboptimal control law considered here in is a proportional plus integral type and is implemented by using only the output variables available from sensor which is also optimally located in a fixed point w.r.t. a moving weld touch.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.534-534
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• 2000

This paper proposes a dynamic compensation scheme for input-constrained feedback linearizable nonlinear systems to cope with the windup phenomenon. Given a feedback linearizing controller for such a nonlinear system designed without considering its input constraint, an additional dynamic compensator is proposed to account for the constraint. This dynamic anti-windup is based on the minimization of a reasonable performance index, and some stability properties of the resulting closed-loop are presented.

• 보건의료산업학회지
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• 제10권2호
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• pp.15-23
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• 2016

Objectives : The purpose of this study was to evaluate the productivity changes of 18 public health centers in Gangwon-do from 2006 to 2013 using the Malmquist Productivity Index(MPI). Methods : Data were collected from Statistics Korea from 2006 to 2013. The input variables were the numbers of medical, nursing and administrative personnels. The output variables were the performances of health promotion programs. Along with the traditional input-oriented DEA analysis, the MPI was calculated. Results : First, among the 18 public health centers, the productivity index of 14 public health centers was increased. Second, the annual productivity showed a 6% increase. Third, the productivity improvements were mainly caused by Scale Efficiency Change. Conclusions : Improving the productivity of public health centers requires the support and external policies of the national and local government. Internally, public health centers need to maintain scale optimization of the center. Additionally, efforts should be made to effectively use limited resources.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• 통상정보연구
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• 제18권1호
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• pp.235-258
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• 2016

본 연구는 산업연관표를 중심으로 2011년~2013년 기간의 실측표기준의 투입산출물표(Input-output Table)를 사용하여 동 기간의 국내 해외직접투자(FDI) 유입액을 한국표준산업분류(KSIC 30부문)기준으로 재분류 및 통합하여 적용한 결과 3개년 평균 국내 외국인직접투자 유입액은 15조 3,000억원이고, 평균총생산유발액은 45조 8,000억원으로 추계되었다. 국내 외국인직접투자 유입의 특징은 감응도계수 및 영향력계수가 큰 산업인 화학제품, 전기 및 전자기기, 금속제품에 편중되어 있다. 특히 중간재로 활용되는 감응도계수가 큰 산업에 국내 외국인직접투자 유치가 이루어지면 국내 경제적 산업파급효과가 큰 것으로 나타난다.

• 한국항만경제학회지
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• 제38권2호
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• pp.31-47
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• 2022

본 연구의 목적은 국가의 ESG 이행 성과와 유관한 세부 지표들을 분류 및 측정할 수 있는 신뢰성 있는 도구를 개발하여 그 적용 가능성에 대한 타당성을 검증하는 것이다. 투입 데이터로서 World Bank의 자료를 토대로 총 239개의 국가를 대상으로 측정한 67개 종류의 ESG 관련 세부 지표를 대상으로 구조방정식의 확인적요인분석과 경로분석을 시행하여 세부지표들을 환경, 사회, 지배구조의 3가지 부문으로 그룹화할 수 있는 최적 모형 도출을 시도하였다. 분석 결과 총 10개의 세부지표들이 국가의 ESG 이행성과와 통계적으로 유의한 관계가 있음을 확인하였다. 또한 해당 세부지표들은 1차 잠재변수인 E, S, G와 모두 양(+)의 상관관계를 보였으며, 모형의 적합도에서도 전반적으로 높은 지수를 보여 변수투입의 타당성 및 신뢰성을 확보하였다. 결과적으로 본 연구는 ESG를 구성하는 다수의 세부 성과 지표들의 잠재변수로의 분류가 가능함을 확인하였으며, 변수의 선정 방법 및 투입 타당성에 대한 명확한 기준을 제시하였다 할 수 있다.