• Title/Summary/Keyword: exact methods

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Fuzzy modeling using transformed input space partitioning

  • You, Je-Young;Lee, Sang-Chul;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.494-498
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    • 1996
  • Three fuzzy input space partitoining methods, which are grid, tree, and scatter method, are mainly used until now. These partition methods represent good performance in the modeling of the linear system and nonlinear system with independent modeling variables. But in the case of the nonlinear system with the coupled modeling variables, there should be many fuzzy rules for acquiring the exact fuzzy model. In this paper, it shows that the fuzzy model is acquired using transformed modeling vector by linear transformation of the modeling vector.

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Hardware Design Methods for Segway Type 2-Wheeled Mobile Robots (세그웨이형 2륜 이동로봇의 하드웨어 설계방법)

  • Joh, Jung-Woo;Park, Gwi-Tae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.5
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    • pp.1-7
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    • 2009
  • In this paper, hardware design methods for segway type 2-wheeled mobile robots are presented. Basically five guide lines are offered to build robots properly for the purpose of experiments; motor selection, battery selection, MCU selection, motor placement, and construction of body. The robots built with these five guide lines will give the best test environment to gain meaningful results in experiments as a precise and exact test-bed.

A Study of Tunnel Position Interpretation using Seismic Travel Time and Amplitude Data Simulation (탄성파 주시 및 진폭 자료의 Simulation에 의한 터널 위치 추적에 관한 연구)

  • Suh, Baek-Soo;Sohn, Kwon-Ik
    • Journal of the Korean earth science society
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    • v.28 no.1
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    • pp.105-111
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    • 2007
  • Seismic and georadar prospecting methods have been used to detect deep seated small tunnel in Korea. The tunnel position interpretation of seismic method has been performed mainly by wave travel time and amplitude. But it was very unstable to interpret the exact tunnel position because of short interval of two measuring boreholes and picking mistake of first arrivals. To solve this problem, this study applied travel-time and amplitude data simulation methods to detect tunnel position.

A Study on the Avioded Generation Costs of Indepndent Power Producers Using Probabilistic Load Decrement Method (확률적 부하감소법을 이용한 민자발전소의 회피비용 계산 방법론 연구)

  • Park, Jong-Bae;Won, Jong-Ryul;Park, Young-Moon
    • Proceedings of the KIEE Conference
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    • 1999.07c
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    • pp.1340-1343
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    • 1999
  • This Paper Presents a new analytic load decrement method for the evaluation of avoided generation costs of independent power producers (IPPs), named as probabilistic load decrement method. Unlike conventional load decrement methods, the proposed method exactly consider the random outage characteristic of a generating unit, economic dispatch order, and the resulting loss of load probability. Therefore, we can Provide the exact generation avoided costs of an IPP by applying the developed method. In the case studies, we have shown the correctness and effectiveness of the method, and compared with conventional load decrement methods.

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A New Convolutional Weighting Function Method for Continuous-time Parameter Identification

  • Park, Hyun-Seob;Park, Poo-Gyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.26.5-26
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    • 2001
  • This paper proposes a new approach to identifying the unknown parameters of continuous LTI systems. For parameter identification in continuous-time systems, the Linear Integral Filter (LIF) method generally has been used in the beginning. Especially, one of the most efficient LIF methods in the literature is to use a weighting function satisfying specific three constraints. In high order systems, even though the weighting function satisfies the three constraints, it is impossible to identify the exact parameters of the systems because of information loss arising from a great amount of magnitude differences among the weighting function and its high-order derivatives. This paper, using an LMI technique, shows the limitation in designing the weighting function of the existing methods, and ...

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Modal Analysis of One Dimensional Distributed Parameter Systems by Using the Digital Modeling Technique (디지털 모델링 기법에 의한 1차원 연속계의 모드 해석)

  • 홍성욱;조종환
    • Journal of KSNVE
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    • v.9 no.1
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    • pp.103-112
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    • 1999
  • A new modeling and analysis technique for one-dimensional distributed parameter systems is presented. First. discretized equations of motion in Laplace domain are derived by applying discretization methods for partial differential equations of a one-dimensional structure with respect to spatial coordinate. Secondly. the z and inverse z transformations are applied to the discretized equations of motion for obtaining a dynamic matrix for a uniform element. Four different discretization methods are tested with an example. Finally, taking infinite on the number of step for a uniform element leads to an exact dynamic matrix for the uniform element. A generalized modal analysis procedure for eigenvalue analysis and modal expansion is also presented. The resulting element dynamic matrix is tested with a numerical example. Another application example is provided to demonstrate the applicability of the proposed method.

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RK- Methods for Robot Application problems

  • Senthilkumar, Sukumar;Lee, Malrey;Kwon, Tae-Kyu
    • International journal of advanced smart convergence
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    • v.2 no.1
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    • pp.18-20
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    • 2013
  • The significance, is to introduce a novel way to employ the improved Runge-Kutta fifth order five stage method, here after called as Modified IRK(5,5) method, for system of second order robot arm problem and variations in angles at the joints in which parameters governing with two degrees of freedom which requires lesser number of function evaluations per time step as compared to the existing ones, in order to save time and spaceAn ultimate aim of this present paper is to solve application problem such as robot arm and initial value problems by applying Runge-Kutta fifth order five stage numerical techniques. The calculated output for robot arm coincides with exact solution which is found to be better, suitable and feasible for solving real time problems.

ABSOLUTELY STABLE EXPLICIT SCHEMES FOR REACTION SYSTEMS

  • Lee, Chang-Ock;Leem, Chae-Hun;Park, Eun-Hee;Youm, Jae-Boum
    • Journal of the Korean Mathematical Society
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    • v.47 no.1
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    • pp.165-187
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    • 2010
  • We introduce two numerical schemes for solving a system of ordinary differential equations which characterizes several kinds of linear reactions and diffusion from biochemistry, physiology, etc. The methods consist of sequential applications of the simple exact solver for a reversible reaction. We prove absolute stability and convergence of the proposed explicit methods. One is of first order and the other is of second order. Numerical results are included.

PRICING EXTERNAL-CHAINED BARRIER OPTIONS WITH EXPONENTIAL BARRIERS

  • Jeon, Junkee;Yoon, Ji-Hun
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.5
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    • pp.1497-1530
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    • 2016
  • External barrier options are two-asset options with stochastic variables where the payoff depends on one underlying asset and the barrier depends on another state variable. The barrier state variable determines whether the option is knocked in or out when the value of the variable is above or below some prescribed barrier level. This paper derives the explicit analytic solution of the chained option with an external single or double barrier by utilizing the probabilistic methods - the reflection principle and the change of measure. Before we do this, we examine the closed-form solution of the external barrier option with a single or double-curved barrier using the methods of image and double Mellin transforms. The exact solution of the external barrier option price enables us to obtain the pricing formula of the chained option with the external barrier more easily.

Bayesian Inference of the Stochastic Gompertz Growth Model for Tumor Growth

  • Paek, Jayeong;Choi, Ilsu
    • Communications for Statistical Applications and Methods
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    • v.21 no.6
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    • pp.521-528
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    • 2014
  • A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.