• Title/Summary/Keyword: optimal estimation

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Application of Particle Swarm Optimization for Harmonic State Estimation (전력시스템 고조파 상태 추정에서 PSO 적용)

  • Wang, Y.P.;Jeong, J.W.;Kim, H.H.;An, B.C.
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.529-530
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    • 2007
  • The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using PSO. This PSO-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using PSO in the HSE.

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Fast Motion Estimation Algorithm using Selection of Candidates and Stability of Optimal Candidates (후보 선별과 최적후보 안정성을 이용한 고속 움직임 예측 알고리즘)

  • Kim, Jong Nam
    • Journal of Broadcast Engineering
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    • v.23 no.5
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    • pp.628-635
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    • 2018
  • In this paper, we propose a fast motion estimation algorithm which is important in video encoding. So many fast motion estimation algorithms have been published for improving prediction quality and computational reduction. In the paper, we propose an algorithm that reduces unnecessary computation, while almost keeping prediction quality compared with the full search algorithm. The proposed algorithm calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, and finds optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain fast computational speed by reducing unnecessary computations. Additionally, the proposed algorithm can be used with conventional fast motion estimation algorithms and prove it in the experimental results.

An Experimental Study on the Optimal Arrangement of Cameras Used for the Robot's Vision Control Scheme (로봇 비젼 제어기법에 사용된 카메라의 최적 배치에 대한 실험적 연구)

  • Min, Kwan-Ung;Jang, Wan-Shik
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.1
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    • pp.15-25
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    • 2010
  • The objective of this study is to investigate the optimal arrangement of cameras used for the robot's vision control scheme. The used robot's vision control scheme involves two estimation models, which are the parameter estimation and robot's joint angle estimation models. In order to perform this study, robot's working region is divided into three work spaces such as left, central and right spaces. Also, cameras are positioned on circular arcs with radius of 1.5m, 2.0m and 2.5m. Seven cameras are placed on each circular arc. For the experiment, nine cases of camera arrangement are selected in each robot's work space, and each case uses three cameras. Six parameters are estimated for each camera using the developed parameter estimation model in order to show the suitability of the vision system model in nine cases of each robot's work space. Finally, the robot's joint angles are estimated using the joint angle estimation model according to the arrangement of cameras for robot's point-position control. Thus, the effect of camera arrangement used for the robot's vision control scheme is shown for robot's point-position control experimentally.

Research for experimental methods of mechanical parameters estimation of the mobile robots (로봇의 기구학적 계수 추정을 위한 실험적 방법에 대한 연구)

  • Choi, Jong-Mi;Park, Joong-Un;Lee, Ji-Hong;Kim, Ji-Yong
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.106-108
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    • 2009
  • In this paper, we handle automatic estimation of mechanical parameters for mobile robots. Most estimation methods are based on the sequence and move-measurement-estimation. Estimated accuracy is largely dependent on the paths. Mathematical conditions minimizing estimation errors are derived, and then a method finding optimal paths for mechanical parameters estimation is proposed.

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Effect of Dimension in Optimal Dimension Reduction Estimation for Conditional Mean Multivariate Regression (다변량회귀 조건부 평균모형에 대한 최적 차원축소 방법에서 차원수가 결과에 미치는 영향)

  • Seo, Eun-Kyoung;Park, Chong-Sun
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.107-115
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    • 2012
  • Yoo and Cook (2007) developed an optimal sufficient dimension reduction methodology for the conditional mean in multivariate regression and it is known that their method is asymptotically optimal and its test statistic has a chi-squared distribution asymptotically under the null hypothesis. To check the effect of dimension used in estimation on regression coefficients and the explanatory power of the conditional mean model in multivariate regression, we applied their method to several simulated data sets with various dimensions. A small simulation study showed that it is quite helpful to search for an appropriate dimension for a given data set if we use the asymptotic test for the dimension as well as results from the estimation with several dimensions simultaneously.

Adaptive Control of CNC Boring Machine by Application of the Variance Perturbation Method (분산 섭동법 에 의한 CNC보오링 머시인 의 적응제어)

  • 이종원
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.8 no.1
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    • pp.65-70
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    • 1984
  • A recursive parameter estimation method is applied to spindle deflection model during boring process. The spindle infeed rate is then determined to preserve the diametral tolerance of bore. This estimation method is further extended to adaptive control by application of the variance perturbation method. The results of computer simulation attest that the proposed method renders the optimal cutting conditions, maintaining the diametral accuracy of bore, regardless of parameter fluctuations. The proposed method necessitating only post-process measurements features that initialization of parameter guess values in simple, a priori knowledge on parameter variations is not needed and the accurate estimation of optimal spindle infeed rate is obtained, even if the parameter estimation may be poor.

Passive Telemetry Sensor System using RLSE Based Real Time Estimation Technique with Optimal Forgetting Factor

  • Lee, Joon-Tark;Kim, Kyung-Yup
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.515-520
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    • 2004
  • In this paper, a passive telemetry RF capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique is proposed. To overcome these trouble problems such as a power limitation and a estimation complexity that the general passive telemetry sensor system including It chip has, the principle of inductive coupling was applied to the modeling of a passive telemetry RF capacitive humidity sensor system and its capacitance was estimatedd by the RLSE algorithm. Specially, by introducing the optimal forgetting factor, we showed that the accuracy of its estimation was improved even in the time varying system and also the convergence time was reduced.

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An Integrated Sequential Inference Approach for the Normal Mean

  • Almahmeed, M.A.;Hamdy, H.I.;Alzalzalah, Y.H.;Son, M.S.
    • Journal of the Korean Statistical Society
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    • v.31 no.4
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    • pp.415-431
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    • 2002
  • A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

Contingency Estimation Method based on Stochastic Earned Value Management System (추계적 EVMS 기반 예비비 산정 방법론)

  • Gwak, Han-Seong;Choi, Byung-Youn;Yi, Chang-Yong;Lee, Dong-Eun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2018.05a
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    • pp.72-73
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    • 2018
  • The accuracy of contingency estimation plays an important role for dealing with the uncertainty of the financial success of construction project. Its' estimation may be used for various purposes such as schedule control, emergency resolve, and quality expense, etc. This paper presents a contingency estimation method which is schedule control specific. The method 1) implements stochastic EVMS, 2) detects a specific timing for schedule compression, 3) identifies an optimal strategy for shortening planned schedule, 4) finds a probability density function (PDF) of project cost overrun, and 5) estimates the optimal contingency cost based on the level of confidence. The method facilitates expeditious decisions involved in project budgeting. The validity of the method is confirmed by performing test case.

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Estimation of Soil Resistivity Parameter for Optimal Grounding Design (최적 접지설계를 위한 대지파라메터의 추정)

  • Lee, Hyung-Soo;Lee, Kwan-Hyung;Lee, Bong-Yong;Shim, Keon-Bo
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.61-63
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    • 1994
  • Accurate estimation of soil resistivity parameters are very important in the design of grounding systems. This paper presents a useful methodology for the optimal estimation of soil parameters based on the weighted least square concepts using a set of earth resistivity measurements by Wenner method. And, this paper developes a computer simulation programming for the estimation of soil parameters. Results are presented and compared with the results of other methods.

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