• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.1-6
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• 2000

This paper presents a control of active suspension for quarter car model with two degree of freedom by using H$\infty$ method. Absolute velocity of car body is measured for feedback. The system parameter variations are treated with multiplicative uncertainty model. Simulation results show that the H$\infty$ control provides good trade-off between ride quality, suspension packaging and road holding constraints. The experiment with a front wheel suspension system was done to verify the simulation results.

• Journal of Environmental Health Sciences
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• v.17 no.2
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• pp.1-8
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• 1991

The stochastic variance and structures of time series data on air quality were examined by employing the techniques of autocorrelation function, variance spectrum, fourier series, ARIMA model. Among the air quality properties of atmosphere, SO$_{2}$ is one of the most siginificant and widely measured parameters. In the study, the air quality data were included hourly observations on SO$_{2}$ TSP and O$_{3}$. The data were measured by automatic recording instrument installed in Kwanghwamoon during February and March in 1991. The results of study were as follows 1. Hourly air quality series varied with the domiant 24 hour periodicity and the 12 hour periodic variation was also observed. 2. The correlation coefficients between SO$_{2}$ and O$_{3}$ is -0.4735. 3. In simulating or forecasting variation in SO$_{2}$ ARIMA models are on a useful tools. The multiplicative seasonal ARIMA (1, 1, 0) (0, 2, 1)$_{24}$ model provided satisfactory results for hourly SO$_{2}$ time series.

• Journal of Ocean Engineering and Technology
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• v.10 no.3
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• pp.153-161
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• 1996

This paper presents a design method of dynamic positioning control system for floating platform with rotatable and retractable thruster using $H_{\infty}$ control technique. The norm band of uncertainty is captured by multiplicative perturbation between nominal model and reduced order model. A controller robust to the uncertainty is designed applying $H_{\infty}$ synthesis. The control law satisfying robust stabillity and nominal performance condition is determined through the mixed sensitivity approach. The evaluation for the resultant controller obtained by $H_{\infty}$ synthesis is done through simulations of the closed loop system. The results of $H_{\infty}$ synthesis are compared to those of the traditional LQ synthesis method.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.126-129
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel type s as states of molecules in a lattice-like physical system defined on a GRF. Because of the MRFGRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular mteractions. The proposed adaptive iterative method was evaluated using simulation data generated by the Monte Carlo method. In the extensive experiments of this study, the proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Journal of Wetlands Research
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• v.1 no.1
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• pp.17-28
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• 1999

The purpose of this study was to analysis water quality monitoring data and to estimate future trends using ARIMA model of time series analysis. Water quality data in Chin yang reservoir were used with monthly monitoring interval during past 7 years. The variations of water quality parameters with periodicity and trend could be estimated by multiplicative ARIMA models and the statistical tests showed a good agreement with the observed data. Therefore, the monthly values of water quality parameters could be forecasted using these models.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1613-1626
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• 2002

This paper presents hybrid control of an active suspension system with a full-car model by using H$\sub$$\infty$/ and nonlinear adaptive control methods. The full-car model has seven degrees of freedom including heaving, pitching and rolling motions. In the active suspension system, the controller shows good performance: small gains from the road disturbances to the heaving, pitching and rolling accelerations of the car body. Also the controlled system must be robust to system parameter variations. As the control method, H$\sub$$\infty$/ controller is designed so as to guarantee the robustness of a closed-loop system in the presence of uncertainties and disturbances. The system parameter variations are taken into account by multiplicative uncertainty model and the system robustness is guaranteed by small gain theorem. The active system with H$\sub$$\infty$/ controller can reduce the accelerations of the car body in the heaving, pitching and rolling directions. The nonlinearity of a hydraulic actuator is handled by nonlinear adaptive control based on the back-stepping method. The effectiveness of the controllers is verified through simulation results in both frequency and time domains.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3381-3388
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• 2012

This research is to find out the method appropriate for the forecasting of passennger demand using seasonal ARIMA model and efficient operation in Jeju National Airport. Time series monthly data for the investigation were collected ranging from January 2003 to December 2011. A total of 108 observations were used for data analysis. Research findings showed that the multiplicative seasonal ARIMA(0.1.2)(0.1.1)12 model is appropriate model. The number of passengers in Jeju National Airport will continue to rise, it was expected to surpass 20 million people.

• Journal of Ginseng Research
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• v.33 no.3
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• pp.240-243
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• 2009

To better understand how to increase a ginseng grower's revenue, a 4-factor revenue determination model (RDM) of raw ginseng production (R=A Y Q P) was proposed. The total revenue (R) is a multiplicative function of four factors: cultivation area(A), unit yield (Y), quality grade (Q) and unit price (P). The A appears to be a pure capital factor. Y and Q are technological factors and P is social and market factor. When P is constant, the technological term (YQ) is the revenue per unit area (R/A) production efficiency per capital. The RDM appears to be a linear model between R and A with the slope [YQ]. RDM was applied to three farmers' raw ginseng production for assessment of its dependency on capital and technological factors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.158-161
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• 2003

A cascade structured neural network called Sigma-Pi$_{t}$ Cascaded Hybrid Neural Network ($\sigma$$\pi$$_{t}$-CHNN) is Proposed. It is an extended version of the Sigma-Pi Cascaded extended Hybrid Neural Network ($\sigma$$\pi$-CHNN), where the classical multiplicative neuron ($\pi$-neuron) is replaced by the translated multiplicative ($\pi$$_{t}$-neuron) model. The learning algorithm of $\sigma$$\pi$$_{t}$-CHNN is composed of an evolutionary programming method, responsible for determining the network architecture, and of a Levenberg-Marquadt algorithm, responsible for tuning the weights of the network. The $\sigma$$\pi$$_{t}$-CHNN is evaluated in 2 pattern classification problems: the 2 spirals and the sonar problems. In the 2 spirals problem, $\sigma$$\pi$$_{t}$-CHNN can generate neural networks with 10％ less hidden neurons than that in previous neural models. In the sonar problem, $\sigma$$\pi$$_{t}$-CHNN can find the optimal solution for the problem i.e., a network with no hidden neurons. These results confirm the expanded information processing capabilities of $\sigma$$\pi$$_{t}$-CHNN, when compared to previous neural network models. network models.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.475-485
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• 1995

In this study, statistical analysis of fatigue data which had obtained from respective 24 fatigue crack, was examined for SiC whisker reinforced aluminium 6061 composite alloy (SiC$_{w}$/A16061) and aluminium 6061 alloy. SiC volume fraction in composite alloy is 25%. The analysis results stress intensity factor range and 0.1 mm fatigue crack initiation life for SiC$_{w}$/A16061 composite & A16061 matrix are the log-normal distribution. And regression analysis by linear model, exponential model and multiplicative model were performed to find out the relationship between fatigue crack growth rate(da/dN) and stress intensity for find out the relationship between fatigue crack growth rate(da/dN) and stress intensity factor range(.DELTA.K) in the SiC$_{w}$/A16061 composite and examine the applicability of Paris' equation to SiC$_{w}$A16061 composite. Also computer simulation was performed for fatigue life prediction of SiC$_{w}$/A16061 composite using the statistical results of this study.udy.