• Title/Summary/Keyword: Input-Output Model

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Estimating the Local Economic Impact of National Natural Recreation Forests Using Regional Input-Output Model (지역산업연관분석을 이용한 국립자연휴양림의 지역경제 파급효과 분석)

  • Han, Sang-Yoel
    • Journal of Korean Society of Forest Science
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    • v.100 no.2
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    • pp.218-225
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    • 2011
  • The purpose of this study is to estimate the economic impacts of National Natural Recreation Forests using a regional input-output (I-O) model. Based on the regional I-O transactions tables developed by Bank of Korea (2009), National Natural Recreation Forests related sectional multipliers were derived with respect to output, income, employment, and value-added. Furthermore, surveys questioned National Natural Recreation Forests visitors in order to estimate per capita expenditures. The result shows that one National Natural Recreation Forests generated 3,380 million Won of output impact, 328 million Won of income impact, 1,017 million Won of value-added impact, and 22 full-time jobs within local effect, respectively. Also, one National Natural Recreation Forests generated 687 million Won of output impact, 85 million Won of income impact, 245 million Won of value-added impact, and 6 full-time jobs outside local effect, respectively.

Invariant Set Based Model Predictive Control of a Three-Phase Inverter System (불변집합에 기반한 삼상 인버터 시스템의 모델예측제어)

  • Lim, Jae-Sik;Park, Hyo-Seong;Lee, Young-Il
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.2
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    • pp.149-155
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    • 2012
  • This paper provides an efficient model predictive control for the output voltage control of three-phase inverter system which includes output LC filters. Use of SVPWM (Space Vector Pulse-Width-Modulation) and the rotating d-q frame is made to obtain an input constrained dynamic model of the inverter system. From the measured/estimated output current and reference output voltage, corresponding equilibrium values of the inductor current and the control input are computed. Derivation of a feasible and invariant set around the equilibrium state is made and then a receding horizon strategy which steers the current state deep into the invariant set is proposed. In order to remove offset error, use of disturbance observer is made in the form of state estimator. The efficacy of the proposed method is verified through simulations.

Comparison Study for Data Fusion and Clustering Classification Performances (다구찌 디자인을 이용한 데이터 퓨전 및 군집분석 분류 성능 비교)

  • 신형원;손소영
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.601-604
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    • 2000
  • In this paper, we compare the classification performance of both data fusion and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. Since the relationship between input & output is not typically known, we use Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: Clustering based logistic regression turns out to provide the highest classification accuracy when input variables are weakly correlated and the variance of data is high. When there is high correlation among input variables, variable bagging performs better than logistic regression. When there is strong correlation among input variables and high variance between observations, bagging appears to be marginally better than logistic regression but was not significant.

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Cable damage identification of cable-stayed bridge using multi-layer perceptron and graph neural network

  • Pham, Van-Thanh;Jang, Yun;Park, Jong-Woong;Kim, Dong-Joo;Kim, Seung-Eock
    • Steel and Composite Structures
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    • v.44 no.2
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    • pp.241-254
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    • 2022
  • The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

Transfer Function Model Forecasting of Sea Surface Temperature at Yeosu in Korean Coastal Waters (전이함수모형에 의한 여수연안 표면수온 예측)

  • Seong, Ki-Tack;Choi, Yang-Ho;Koo, Jun-Ho;Lee, Mi-Jin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.5
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    • pp.526-534
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    • 2014
  • In this study, single-input transfer function model is applied to forecast monthly mean sea surface temperature(SST) in 2010 at Yeosu in Korean coastal waters. As input series, monthly mean air temperature series for ten years(2000-2009) at Yeosu in Korea is used, and Monthly mean SST at Yeosu station in Korean coastal waters is used as output series(the same period of input). To build transfer function model, first, input time series is prewhitened, and then cross-correlation functions between prewhitened input and output series are determined. The cross-correlation functions have just two significant values at time lag at 0 and 1. The lag between input and output series, the order of denominator and the order of numerator of transfer function, (b, r, s) are identified as (0, 1, 0). The selected transfer function model shows that there does not exist the lag between monthly mean air temperature and monthly mean SST, and that transfer function has a first-order autoregressive component for monthly mean SST, and that noise model was identified as $ARIMA(1,0,1)(2,0,0)_{12}$. The forecasted values by the selected transfer function model are generally $0.3-1.3^{\circ}C$ higher than actual SST in 2010 and have 6.4 % mean absolute percentage error(MAPE). The error is 2 % lower than MAPE by ARIMA model. This implies that transfer function model could be more available than ARIMA model in terms of forecasting performance of SST.

Multi-Input Multi-Output Nonlinear Autopilot Design for Ship-to-Ship Missiles

  • Im Ki-Hong;Chwa Dong-Kyoung;Choi Jin-Young
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.255-270
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    • 2006
  • In this paper, a design method of nonlinear autopilot for ship-to-ship missiles is proposed. Ship-to-ship missiles have strongly coupled dynamics through roll, yaw, and pitch channel in comparison with general STT type missiles. Thus it becomes difficult to employ previous control design method directly since we should find three different solutions for each control fin deflection and should verify the stability for more complicated dynamics. In this study, we first propose a control loop structure for roll, yaw, and pitch autopilot which can determine the required angles of all three control fins. For yaw and pitch autopilot design, missile model is reduced to a minimum phase model by applying a singular perturbation like technique to the yaw and pitch dynamics. Based on this model, a multi-input multi-output (MIMO) nonlinear autopilot is designed. And the stability is analyzed considering roll influences on dynamic couplings of yaw and pitch channel as well as the aerodynamic couplings. Some additional issues on the autopilot implementation for these coupled missile dynamics are discussed. Lastly, 6-DOF (degree of freedom) numerical simulation results are presented to verify the proposed method.

The Contribution for Industry of Renewable Energy Human Resource Development Programs using Supply-Side Input-Output Model (인력공급지장의 측면으로 본 신재생에너지 인력양성의 산업기여도 분석)

  • Lee, You-Ah;Kim, Jin-Soo;Heo, Eun-Nyeong
    • 한국신재생에너지학회:학술대회논문집
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    • 2009.11a
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    • pp.264-269
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    • 2009
  • 신재생에너지기술 개발인력 확보는 국가의 지속적인 성장을 가능하게 하는 주요 요인이다. 본 연구에서는 신재생에너지인력양성이 원활하게 공급되지 않았을 경우 발생할 수 있는 인력공급지장효과를 분석하기 위하여 산업연관분석의 공급유도모형을 유도하고 2006년 신재생에너지 인력양성사업 배출인원을 기준으로 실증분석을 실시하였다. 또한 공급유도형의 감응도 계수와 영향력계수 분석을 통해 신재생에너지 관련 사업과 타 산업간의 전후방연쇄효과를 비교분석하였다. 연구 수행 결과 신재생에너지 관련 산업의 평균 영향력 계수는 1.37, 평균 감응도 계수는 0.96으로 최종 수요적 제조업의 성격을 띠고 있는 것으로 나타났다. 또한, 2006년 신재생에너지 인력양성사업에 의해 배출된 336명의 인력이 공급되지 않았을 경우 공급지장비용은 총 230억이며, 8개 신재생에너지원 중 태양열과 연료전지에 인력 공급지장비용이 타 에너지원에 비해 상대적으로 높은 것으로 분석되었다. 산업분류 기준으로는 일반목적용 기계산업과 전기기계 장치 산업이 신재생 에너지 인력공급 장애에 따른 지장비용이 높은 것으로 분석되었다.

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Model Reference Adaptive Control for Multivariable Systems (다변수 시스템에 대한 기준 모델형 적응 제어)

  • Hai-Won Yang
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.32 no.11
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    • pp.394-403
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    • 1983
  • This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

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A Study on Evaluating the Efficiency of the Photonics Industry in Gwangju Using a DEA Model (DEA 모형을 활용한 광주 광산업체 효율성 평가에 관한 연구)

  • Cho, Geon;Jung, Kyung-Ho
    • Journal of Korean Society for Quality Management
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    • v.39 no.2
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    • pp.244-255
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    • 2011
  • In this study, we try to evaluate the efficiency of the photonics industry using a data envelopment analysis(DEA) model. We first develope four stage procedures for selecting proper input and output variables which consist of selecting the first candidate variables from literature survey, selecting the second candidate variables through experts' discussion, measuring the partial efficiency of the selected variables based on Tofallis' profiling, and clustering some variables through the rank correlation analysis of partial efficiency proposed by Min and Kim(l998). With this procedure, we select 4 input variables(capital, number of employee, R&D cost, operating cost) and 2 output variables(sales, growth of sales) and then utilize CCR and BCC model to measure efficiencies of 26 photonics companies in Gwangju. Moreover, we perform the reference group analysis to figure out what causes inefficiencies and to provide the desirable values for input and output variables at which inefficient photonics companies become efficient. Finally, we classify 26 photonics companies into three groups such as optical communications, optical applications, and optical sources, and perform the Kruskal-Wallis test to check if there exist some differences between efficiencies of three groups.

Analyzing the Industrial Contribution of Human Resource Development Programs in Renewable Energy Sector using Supply-side Input-Output Model (인력공급지장의 측면으로 본 신재생에너지 인력양성의 산업기여도 분석)

  • Lee, You-Ah;Kim, Jin-Soo;Heo, Eun-Nyeong
    • New & Renewable Energy
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    • v.5 no.4
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    • pp.68-73
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    • 2009
  • 국가 에너지 안보 확보와 친환경적이고 지속적인 '저탄소 녹색성장'의 기반을 마련한다는 측면에서 신재생에너지 분야의 인력양성은 시급하고도 중요한 당면 과제이다. 본 연구에서는 신재생에너지인력양성이 원활하게 공급되지 않았을 경우 발생할 수 있는 인력공급지장효과를 분석하기 위하여 산업연관분석의 공급유도모형을 유도하고 2006년 신재생에너지 인력양성사업 배출인원을 기준으로 실증분석을 실시하였다. 또한 공급유도형의 감응도 계수와 영향력계수 분석을 통해 신재생에너지 관련 사업과 타 산업 간의 전후방연쇄효과를 비교분석하였다. 연구 수행 결과 신재생에너지 관련 산업의 평균 영향력계수는 1.37, 평균 감응도 계수는 0.96으로 최종 수요적 제조업의 성격을 띠고 있는 것으로 나타났다. 또한, 2006년 신재생에너지 인력양성사업에 의해 배출된 336명의 인력이 공급되지 않았을 경우 공급지장비용은 총 230억이며, 8개 신재생에너지원 중 태양열과 연료전지에 인력 공급지장비용이 타 에너지원에 비해 상대적으로 높은 것으로 분석되었다. 산업분류 기준으로는 일반목적용 기계 산업과 전기기계 장치 산업이 신재생 에너지 인력공급 장애에 따른 지장비용이 높은 것으로 분석되었다.

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