• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.159-167
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• 2000

The purpose of this study is to estimate the stochastic monthly runoff model for the Kunwi south station of Wi-stream basin in Nakdong river system. This model was based on the theory of Box-Jenkins multiplicative ARlMA and the state-space model to simulate changes of monthly runoff. The forecasting monthly runoff from the pair of estimated effective rainfall and observed value of runoff in the uniform interval was given less standard error then the analysis only by runoff, so this study was more rational forecasting by the use of effective rainfall and runoff. This paper analyzed the records of monthly runoff and effective rainfall, and applied the multiplicative ARlMA model and state-space model. For the P value of V AR(P) model to establish state-space theory, it used Ale value by lag time and VARMA model were established that it was findings to the constituent unit of state-space model using canonical correction coefficients. Therefore this paper confirms that state space model is very significant related with optimization factors of VARMA model.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.111-116
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• 2006

Given a state, it is essential to for the finite state model analysis (such as model checking) to decide whether or not the state is reachable. W a site of the model is small, the whole state space is to be explored exhaustively. However, it is very difficult or even impossible if a size of the model is large. In this case, the model can be reduced into a smaller one via abstraction which does not allow e false positive error. this paper, we devise such an abstraction and apply it to the Nemorize game solving. As a result, unsolved game due to the state explosion problem is solved with the proposed abstraction.

• Structural Engineering and Mechanics
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• v.33 no.2
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• pp.257-260
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• 2009

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.344-349
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• 2005

In conventional small signal stability analysis, the system is assumed to be invariant and the state space equations are used to calculate the eigenvalues of the state matrix. However, when a system contains switching elements such as FACTS equipments, it becomes a non-continuous system. In this case, a mathematically rigorous approach to system small signal stability analysis is performed by means of eigenvalue analysis of the system's periodic transition matrix based on the discrete system analysis method. In this paper, the RCF (Resistive Companion Form) method is used to analyze the small signal stability of a non-continuous system including switching elements. Applying the RCF method to the differential and integral equations of the power system, generator, controllers and FACTS equipments including switching devices should be modeled in the form of state transition equations. From this state transition matrix, eigenvalues that are mapped into unit circles can be computed precisely.

• Korean Institute of Interior Design Journal
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• v.14 no.1
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• pp.160-167
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• 2005

The paper raises a question in argument about the method of creating space depending on accidental creation by computer as the method of describing movement pattern, and emphasizes the role of the mathematics which may change the shape into the image or reflection, that is, data which human may understand and expect. If the mathematics could be the method of describing movement pattern, it may play a important role on the analysis of architectural space based on the idea of post-constructionism, which is likely to consider the modern architectural space recognized as the sequential frames containing movement, as the suspended state of the moving object. And then, this infinite series, 'the sum' of the suspended state, is not studied mathematically and scientifically, but is able to be shaped by reviewing the validity in mathematics about the nonlinear space. This is, therefore, the fundamental research in order to define the role of the mathematics in formation of space of contemporary architecture.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.119-129
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• 1995

In this paper, we propose a schedulatility analysis method for real-time programs. Several approaches to anlayzing schedulability have been developed, but since these approaches use a fixed priority scheduling method and/or traverse all possible state spaces, there take place exponential time and space complexity of these methods, Therefore it is necessary to reduce the state space and detect schedulability at earlier time. Our schedulability analysis method uses a minimum unit time taken to terminate synchronization action, a minimum unit time taken to terminate actions after synchronization, and a deadline of processes to detect unschedulability at earlier time and dynamic scheduling scheme to reduce state space. We conclude that our method can detected unschedulability earlier 50 percent unit time than Fredette's method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.209-221
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• 1999

Several approaches to anlayzing real-time schedulability have been presented, but since these used a fixed priority scheduling scheme and/or traverse all possible state spaces, there take place exponential time and space complexity of these methods. Therefore it is necessary to reduce the state space and detect schedulability at earlier time. This paper proposes and implements an advanced schedulability analysis algorithm to determine that is satisfied a given deadlines for real-time processes. These use a minimum execution time of process, periodic, deadline, and a synchronization time of processes to detect schedulability at earlier time and dynamic scheduling scheme to reduce state space using the transition rules of process algebra. From a result of implementation, we demonstrated the effective performance to determine schedulability analysis.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.169-171
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• 1994

This paper is to find out more reliable analyzing method of heart rate variability. Heart rate variability analysis is to evaluate cardiovascular stability and also have used as an indicator of autonomic nervous system activity. In this study, time domain analysis, spectral analysis and state space analysis method are applied to analyze heart rate variability. Because of nonlinear characteristics of heart rate, we need not only spectral analysis, but also state space analysis. Fractal dimension of spectral estimation is useful indicator of autonomic nervous activity.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.387-396
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• 2009

The life and performance of lithium battery are greatly influenced by the formation process which is essential in the process of manufacture. Charge/discharge system for the lithium battery are required for the formation process. To simulate such a system in a conventional method takes very long time and requires huge memory space to save data files. So the simulation may be impossible with a general-purpose PC. In this paper, the lithium battery is modelled to a resistor-capacitor serial circuit and the lithium battery charge/discharge system is analyzed and simulated by using state space averaging method. As a result, the simulation time is reduced dramatically and the simulation of the lithium battery charge/discharge system becomes possible on a general-purpose PC within 3 hours. Also, both the charge/discharge characteristics and the time required to charge/discharge of the lithium battery charge/discharge system can be observed. To verify the propriety of resistor-capacitor serial circuit modeling method for lithium battery and the validity of the analysis and simulation based on state space averaging, the lithium battery charge/discharge system is composed and experimentations are carried out.

• Smart Structures and Systems
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• v.14 no.1
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• pp.17-37
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• 2014

In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.