• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.71-79
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• 2016

This study proposes a performance model of a shared bus multi-processor system and analyzes the effect of input/output types on system performance and overload of shared resources. This system performance model reflects the memory reference time in relation to the effect of input/output types on shared resources and the input/output processing time in relation to the input/output processor, disk buffer, and device standby places. In addition, it demonstrates the contribution of input/output types to system performance for comprehensive analysis of system performance. As the concept of workload in the probability theory and the presented model are utilized, the result of operating and analyzing the model in various conditions of processor capability, cache miss ratio, page fault ratio, disk buffer hit ratio (input/output processor and controller), memory access time, and input/output block size. A simulation is conducted to verify the analysis result.

• Management & Information Systems Review
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• v.20
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• pp.137-156
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• 2007

This study had an objective to obtain a result of the economic impacts of lodging industry on the Koran economy. Using the input-output model(I-O model), lodging industry sectoral multipliers were derived from the effects of output, income, employment, value added. indirect tax, and import. According to results of this study, estimated economic impacts of the convention industry were $2,950 million in output, $712 million in income, 92,257persons in employment, $1,590 million in value added, $12 million in indirect tax, and $226 million in import sectors.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1435-1437
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• 2003

In this paper, we proposed static output feedback model predictive control for Wiener models. We adopted polytopic uncertainty description of Wiener Model Predictive Control (WMPC) algorithms for considering output nonlinearities. Robust stability conditions have been presented under which the closed loop stability of static output feedback MPC is guaranteed. The proposed control law is determined from the static output feedback WMPC based on the current estimated state with explicit satisfaction of input constraints.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.432-441
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• 2016

Solar energy is the ideal power choice for long-endurance stratospheric airships. The output performance of solar array on stratospheric airship is affected by several major factors: flying latitude, flight date, airship's attitude and the temperature of solar cell, but the research on the effect of these factors on output performance is rare. This paper establishes a new simplified analytical model with thermal effects to analyze the output performance of the solar array. This model consisting of the geometric model of stratospheric airship, solar radiation model and incident solar radiation model is developed using MATLAB computer program. Based on this model, the effects of the major factors on the output performance of the solar array are investigated expediently and easily. In the course of the research, the output power of solar array is calculated for five airship's latitudes of $0^{\circ}$, $15^{\circ}$, $30^{\circ}$, $45^{\circ}$ and $60^{\circ}$, four special dates and different attitudes of five pitch angles and four yaw angles. The effect of these factors on output performance is discussed in detail. The results are helpful for solving the energy problem of the long endurance airship and planning the airline.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• Atmosphere
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• v.28 no.3
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• pp.247-261
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• 2018

The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.183-193
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• 2007

This paper shows that a response function for the center of fuzzy output nay not be the same as that for the spread in a fuzzy linear regression model and then suggests a separate fuzzy regression model makes a distinction between response functions of the center and the spread of fuzzy output. Also we use a least squares method to estimate the separate fuzzy regression model and compare an accuracy of proposed model with another fuzzy regression model developed by Diamond (1988) and Kao and Chyu (2003).

• Journal of Sensor Science and Technology
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• v.20 no.6
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• pp.375-381
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• 2011

Ionic polymer-metal composite(IPMC) consists of an ion conductive membrane plated by metallic electrodes on both surfaces. When it bends, a voltage is generated between two electrodes. Since IPMC is flexible and thin, it can be easily mounted on the various surfaces of a body. The present study investigates a sensor system using IPMC to effectively detect the bending angles applied on IPMC sensor. The paper evaluates several R and C circuit models that describe the physical composition of IPMC and selects the best model for the detection of angles. The circuit models implemented with a charge model describe the relationship between input bending angles and output voltages. The identification of R and C values was performed by minimizing the error between the real output voltages and the simulated output voltages from the circuit models of IPMC sensor. Then the output signal of a sensor was fed into the inverse model of the identified model to reproduce the bending angles. In order to support the validation of the model, the output voltages from an arbitrary bending motion were also applied to the selected inverse model, which successfully reproduced the arbitrary bending motion.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1874-1885
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• 2018

The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.