• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.94-102
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• 2012

Recently, the global financial crisis and the increasing number of unsold houses in Korea are construction companies to assess their efficiency. The most important factor in analyzing the efficiency of a company is the input-output variable. However, systematic stud the core input-output variables, which have a great influence on the efficiency analysis. Thus, to the core input-output variables for efficiency analysis of construction companies, this study propose a model that includes all combinations of input-output variables and to find the core input-output variables using the Data Envelopment Analysis(DEA) model and Principal Component Analysis(PCA). Existing research and theories were studied variables and 21 models were established to measure efficiency. were obtained that the core input and output variable in 2006 the number of employees and sales. For 2008, the core input variable was capital stock and the core output variable was quarterly net profit. For 2010, the core input variable was fixed asset and the core output variable was sales. Through obtaining the variables that greatly affect the efficiency of construction companies, it is considered that individual construction companies will be able to prepare a priority strategy to enhance efficiency.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.

• STI Policy Review
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• v.1 no.2
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• pp.51-68
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• 2010

This paper compares OECD nations by developing a comprehensive evaluation index that examines the efforts and achievements of countries toward Low-Carbon Green Growth. The input-process-output of a Low-Carbon Society system is in dynamic competition with that of a High-Carbon Society system. The model used in this study of the comprehensive evaluation index for Low-Carbon Green Growth was comprised of Large indices such as Input, Process, and Output. The Input and Output consisted of 'Social-economic' and 'Physical-ecological' Middle indices while the Process was made up of 'Stimulation mechanisms' and 'Participation of stakeholders and Knowledge flow' Middle indices. In order to calculate the comprehensive evaluation index, our model gave a weight to each indicator/index and applied a weighted arithmetic mean. Korea ranked $15^{th}$ out of 30 OECD nations in the comprehensive evaluation that analyzed Input ($14^{th}$), Process ($18^{th}$), and Output ($17^{th}$). The top five nations were Switzerland, Sweden, Denmark, Germany, and France; while Japan was $8^{th}$ and the USA $26^{th}$.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.789-798
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• 2016

Frequent algal blooms at major river systems in Korea have been serious social and environmental problems. Especially, the appearance of cyanobacteria with toxic materials is a threat to secure a safe drinking water. In order to model the behaviour of cyanobacteria cell number, an exclusive causality analysis using prewhitening technique was introduced to delineate effective parameters to predict the cell numbers of cyanobacteria in Seungchon Weir and Juksan Weir along Youngsan river system. Both input and output transfer function models were obtained to explain temporal variation of cyanobacteria cell number. A threshold behaviour of water temperature was implemented into the model development to consider winter characteristic of cyanobacteria. The implementation of water temperature threshold into the model structure improves the predictability in simulation. Even though the input output transfer model cannot completely explained all blooms of cyanobacteria, the simple structure of model provide a feasibility in application which can be important in practical aspect.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1222-1227
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• 1990

The problem of identification of continuous systems is considered when both the discrete input and output measurements are contaminated by white noises. Using a predesigned digital low-pass filter, a discrete-time estimation model is constructed easily without direct approximations of system signal derivatives from sampled data. If the pass-band of the filter is designed so that it includes the main frequencies of both the system input and output signals in some range, the noise effects are sufficiently reduced, accurate estimates can be obtained by least squares(LS) algorithm in the presence of low measurement noises. Two classes of filters(infinite impulse response(IIR) filter and finite impulse response(FIR) filter) are employed. The former requires less computational burden and memory than the latter while the latter is suitable for the bias compensated least squares(BCLS) method, which compensates the bias of the LS estimate by the estimates of the input-output noise variances and thus yields unbiased estimates in the presence of high noises.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.5
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• pp.398-412
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• 2023

The Korean government is actively promoting the hydrogen industry as a key driver of economic growth. This commitment is evident in the 2019 hydrogen economy activation roadmap and the 2021 basic plan for hydrogen economy implementation. This study quantitatively analyzes the economic impact of the hydrogen economy using input-output analysis based on the Bank of Korea's 2019 input-output table, projecting its size by 2050. Four parts dealt with production-inducing, value-added creation, employment-inducing, and wage-inducing based on a demand-driven model. The results reveal that transportation had the most remarkable economic effect throughout the hydrogen economy, and production was the least. The hydrogen economy is projected to reach 71.2 trillion won by 2050.

• Korean Management Science Review
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• v.15 no.2
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Management & Information Systems Review
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• v.5
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• pp.81-101
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• 2000

The purpose of this comparative study is to compare and evaluate venture business of electronic and communication industry by Data Envelopment Analysis(DEA). DEA is a linear programming-based technique that converts multiple input and output measures into a single comprehensive measures of productive efficiency. In this paper, the CCR model and trend analysis model are used to examine the efficiency of 18 venture business. Input variables are number of employees. raw-material costs and production capability and output variables are real production, sales revenues and net income after taxes. DEA approach broad information like as efficiency level of each Decision Making Unit(DMU), reference group of efficiency improvement and trends of efficiency shift. Finally, the correlation of input and output variables are examined to examine the relationship among variables.