• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.129-133
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• 2005

This paper discusses DC/DC converter modeling using average model of switch and critical characterist. Average model of switch approach is expended to the modeling of boundary conduction mode DC/DC converters that operate at the boundary between Continuous Conduction Mode(CCM) and Discontinuous Conduction Mode(DCM). Frequency responses predicted by the average model of switch are verified by simulation and experiment.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.259-269
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• 1993

A moving average model, LMA(q) and an autoregressive-moving average model, NLARMA(p, q), with Laplacian marginal distribution are constructed and their properties are discussed; Their autocorrelation structures are completely analogus to those of Gaussian process and they are partially time reversible in the third order moments. Finally, we study the mixing property of NLARMA process.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.3
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• pp.290-296
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• 2014

This paper presents a design strategy for the control of the Z-source inverter (ZSI). For the Z-network capacitor voltage control, the average current model is derived to describe the dynamics of the voltage control and the controller outputs the average current command for the capacitor. Z-network inductor current reference is derived from the average current model of the Z-network capacitor. The inner current control loop outputs the average voltage command for the Z-network inductor and the shoot-through duty ratio of the ZSI is calculated from the output using the average voltage model of the Z-network inductor. The gain values of the current and voltage controllers are directly obtained by the Z-network parameters and desired bandwidth of each controller without a gain tuning process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1358-1361
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• 2003

In this study, intrinsic static/dynamic fracture toughness of Al 7175-T74 are evaluated from the apparent static/dynamic toughness of notched specimen. The notch/crack critical average stress fracture model is suggested to establish the relationship to predict the intrinsic fracture toughness from the apparent fracture toughness of a notched specimen. The notch/crack critical average stress fracture model is established using the relation between the notch root radius and the effective distance calculated by finite element analysis. It is conclude that the true fracture toughness can be estimated from test results of apparent fracture toughness measured by using a notched specimen. Also, critical notch root radius can be predicted by notch/crack critical average stress fracture model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.3
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• pp.285-291
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• 2014

This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

• Korean Journal of Health Education and Promotion
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• v.12 no.2
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• pp.36-47
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• 1995

This research was obtained from analyzing how the physiques of the 3rd grade students of high school for males and females and developed for the last eleven years(from 1983 to 1993). By the physiques and nutritional index of physical growth and development, Relative Body Weight of 36.62 exceeded the standard, on the other hand females showed lower records than the standard. Relative Chest Girth Index belonged to the normal type of males and females in all, in the comparison of the records between 1983 and 1993, males increased in average 0.29 and females in average 0.55. Relative Chest Girth Index of females was greater than that of females. By the results of Relative Sitting Height Index, growth of the lower body for males and females was greater than that of males. In case of Vervaeck Index, males increased in average 2.04 but females increased in average 1, 20 relatively less than males. These phenomena provided for the evidence of the deficient nutrition in females. In the regression models of body height and body weight within a certain period, statistical regression model types which best indicated chronological average changes of body height and body weight, took 3rd Order Polynomial Regression Model rather than linear regression model. In females, statistical regression model types which best is suitable for chronological average change of body height and body weight, took 4th and 2nd Order Polynomial Regression Model respectively. The prediction value of 1995 by estimated polynomial regression model anticipated that body height of 3rd grade year students of high school of males in 1993 went on increasing from 170.87cm to 171.79cm in average 0.92cm growth and that of females from 158.99cm to 160.79cm in average 1.80cm growth. In addition, body weight of males seemed to increase from 62.58kg to 64.52kg in average 1.94kg growth and that of females seemed to increase from 54.05kg to 54.19kg in average 0.14kg growth. Linear Regression Model was suitable for the regression model of body weight for body height. Prediction on increase of an average body weight for body height was that, according to growth of body height 1cm in males, body weight increased 1.41kg averagely and that of females 0.86kg. For that reason, we came to conclusion that body weight increase for body height 1cm in males was greater than that in females on average.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.6
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• pp.34-43
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• 2008

The state-space average model is extended to buck-boost, and buck-boost topology switching mode DC/DC converters and modified to have higher precision without increment of computation. The modified model is used in continuous conduction mode(CCM) switching DC/DC converters and some significant conclusions are derived. This paper discusses the discontinuous conduction mode(DCM) modeling of DC/DC converter and critical characteristic using average model of switch. Average model of switch approach is expended to the modeling of boundary conduction mode DC/DC converters that operate at the boundary between continuous conduction mode(CCM) and discontinuous conduction mode(DCM). Frequency responses predicted by the average model of switch are verified by simulation and experiment. A prototype featuring 15[V] input voltage, 24[V] output voltage, and 24[W] output power using MOSFET.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.985-987
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using individual average difference. In order to accurately recognize an user' s emotion, the proposed model utilizes the difference between the average of the given input physiological signals and the average of each emotion state' signals rather than only the input signal. For the purpose of alleviating data sparse -ness, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of physiological signals based on a second rather than the longer total emotion response time. With the aim of easily constructing the model, it utilizes a simple average difference calculation technique and a maximum entropy model, one of well-known machine learning techniques.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.41-49
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• 2016

To evaluate lubrication properties by surface roughness under boundary and mixed lubrication, a new approach is suggested by both asperity flow and contact with stochastic characteristics. Many researchers already have studied the effect of surface roughness on flow. But, it has become important to research of the phenomenon of asperities contact in surfaces because the growth of asperities contact area under heavy load conditions. In this paper, flow factors in the average flow model derived by Patir and Cheng were used, and a multi-asperity contact model was included to calculate lubrication properties of a surface with a randomly generated rough surface. A numerical analysis using the average Reynolds equation with both the average flow model and the asperity contact model was conducted, and the results were compared with those from previous research. The results showed that the influence of asperities on lubrication and the friction coefficient changed rapidly on application of contact model.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.9-21
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• 2020

The aim of this paper is to predict the Borsa Istanbul (BIST) 30 index movements to determine the most accurate buy and sell decisions using the methods of Artificial Neural Networks (ANN) and Genetic Algorithm (GA). We combined these two methods to obtain a hybrid intelligence method, which we apply. In the financial markets, over 100 technical indicators can be used. However, several of them are preferred by analysts. In this study, we employed nine of these technical indicators. They are moving average convergence divergence (MACD), relative strength index (RSI), commodity channel index (CCI), momentum, directional movement index (DMI), stochastic oscillator, on-balance volume (OBV), average directional movement index (ADX), and simple moving averages (3-day moving average, 5-day moving average, 10-day moving average, 14-day moving average, 20-day moving average, 22-day moving average, 50-day moving average, 100-day moving average, 200-day moving average). In this regard, we combined these two techniques and obtained a hybrid intelligence method. By applying this hybrid model to each of these indicators, we forecast the movements of the Borsa Istanbul (BIST) 30 index. The experimental result indicates that our best proposed hybrid model has a successful forecast rate of 75%, which is higher than the single ANN or GA forecasting models.