• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.14
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• pp.49-58
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• 1986

Those facts I have studied on the theoretical characteristics of stock price earning ratio related with firm evaluation are as followings. First, I have investigated stock valuation analysis under certainty in view of Miller's, Modigliani's and Linter's theories in Chapter Ⅱ, and it is found that stock valuation under uncertainty to which the basic model of MM theory and the concept of capitalization ratio are applied is the same output, as in the case under certainty. And I have examined the stock valuation of growth corporations in which net investment, total capitals and operating profits are expected. Second, I have reexamined the fact that stock price profits are the erotical indices of firm valuation and the firm valuation on the basis of stock price earning ratio in Chapter III. As a whole, I have surveyed the stock price earning ratio theory of the growth stocks and there have been found some problems as such scholars as Malkiel and others have suggested focusing on the stock price structure of growth stocks. To conclude, there must be incessant efforts for the study of security analysis to make it develop ideally.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.12
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• pp.1287-1293
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• 2013

In this paper, we consider variable speed wind turbine systems containing uncertain elements. Though PI controller is generally used for pitch control, it cannot guarantee a stability and performance of the complicated wind turbine systems. A robust pitch control scheme is proposed to regulate the electric power output above the rated wind speed. The pitch controller is designed in order to guarantee uniform boundedness and uniform ultimate boundedness based on the bound values of the set where the uncertainties are laid or moves. In order to verify the proposed control scheme, we present stability analysis and simulation results using Matlab/Simulink.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1183-1187
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• 2011

In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1511-1512
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• 2008

본 논문에서는 불확실성을 가지는 2차원 비선형 시스템을 안정화하기 위해서 추가 다이나믹스를 이용하여 출력 궤환 제어기법을 제안한다. 추가 다이나믹스는 이득값에 대한 것으로 0으로 수렴하는 구조를 지니고 있으며, 이 상태변수의 역수가 고이득의 역할을 함으로써 불확실성이 존재함에도 불구하고 제어목표를 이룰 수 있다. 더욱이 추가 다이나믹스는 그 설계에 의해 목표달성 후에는 본래의 초기값으로 복귀하는 구조를 지니고 있다.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.281-285
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• 2009

Mobile robot has various sensors for describing the external world. The ultrasonic sensor widely applied to the most mobile robot to detect the obstacle and environment owing to low cost, its easy to use. However, ultrasonic sensor has major problems: the uncertainty information of sensor, false readings caused by specular reflection, multi path effect, low angular resolution and sensitivity to changes in temperature and humidity. This paper describes a sensor system for map building of mobile robot. It was made of low cost PSD (Position Sensitive Detector) sensor array and high speed RISC MPU. PSD sensor is cost effective and light weighting but its output signal has many noises. We propose heuristic S/W filter to effectively remove these noises. The developed map building sensor system was equipped on a mobile robot and was compared with ultrasonic sensor through field test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1597-1600
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• 2010

In this paper, a direct controller for nonlinear plants using a neural network is presented. The composed of the control input by using RBF neural networks and auxiliary input to compensate for effects of the approximation errors and disturbances. In the results, using this scheme, the output tracking error between the plant and the reference model can asymptotically converge to zero in the presence of bounded disturbances and approximation errors. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.599-605
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• 2014

This paper presents the interactive behavior modeling method based on POMDP (Partially Observable Markov Decision Process) for HRI (Human-Robot Interaction). HRI seems similar to conversational interaction in point of interaction between human and a robot. The POMDP has been popularly used in conversational interaction system. The POMDP can efficiently handle uncertainty of observable variables in conversational interaction system. In this paper, the input variables of the proposed conversational HRI system in POMDP are the input information of sensors and the log of used service. The output variables of system are the name of robot behaviors. The robot behavior presents the motion occurred from LED, LCD, Motor, sound. The suggested conversational POMDP-based HRI system was applied to an emotional robot KIBOT. In the result of human-KIBOT interaction, this system shows the flexible robot behavior in real world.

• Korean Journal of Veterinary Research
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• v.46 no.2
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• pp.159-164
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• 2006

A stochastic simulation model incorporated with Reed-Frost approach was derived for evaluating diagnostic performance of a test used for a screening program of an infectious disease. The Reed-Frost model was used to characterize the within-herd spread of the disease using a hypothetical example. Specifically, simulation model was aimed to estimate the number infected animals in an infected herd, in which imperfect serologic tests are performed on samples taken from herds and to illustrate better interpreting survey results at herd-level when uncertainty inevitably exists. From a risk analysis point of view, model output could be appropriate in developing economic impact assessment models requiring probabilistic estimates of herd-level performance in susceptible populations. The authors emphasize the importance of knowing the herd-level diagnostic performance, especially in performing emergency surveys in which immediate control measures should be taken following the survey. In this context this model could be used in evaluating efficacy of a survey program and monitoring infection status in the area concerned.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.32-35
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• 2011

The economic value of a wind farm project is influenced by various risk factors such as wind power output and electricity market price. In particular, there is uncertainty in the economic evaluation of a wind farm project due to uncertain wind power outputs, which are fluctuated by weather factors such as wind speed, and volatile electricity market prices. This paper presents a systematic method to assess the economic value and payback period of a wind farm project using Least Square Monte-Carlo (LSMC) simulation. Numerical example is presented to validate the effectiveness of the proposed economic assessment method for a wind farm project.