• Title/Summary/Keyword: weighting factor

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Database Investigation Algorithm for High-Accuracy based Indoor Positioning (WLAN 기반 실내 위치 측위에서 측위 정확도 향상을 위한 데이터 구축 방법)

  • Song, Jin-Woo;Hur, Soo-Jung;Park, Yong-Wan;Yoo, Kook-Yeol
    • IEMEK Journal of Embedded Systems and Applications
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    • v.7 no.2
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    • pp.85-93
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    • 2012
  • In this paper, we proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyse the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLAN-based positioning methods because it has high location accuracy compare to other indoor positioning methods. The fingerprint method has different location accuracies which depend on training phase and positioning phase. In training phase, intensity of RSSI is measured under the various. Conventional systems adapt average of RSSI samples in a database construction, which is not quite accurate due to variety of RSSI samples. In this paper, we analyse WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.

Determination of Nesting Algorithm Fitness Function through Various Numerical Experiments (수치 실험을 통한 조선 강판 전용 Nesting Algorithm의 적합도 함수의 결정)

  • Lee, Hyebin;Ruy, WonSun
    • Journal of Ocean Engineering and Technology
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    • v.27 no.5
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    • pp.28-35
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    • 2013
  • In this paper, a research on the composition of the nesting algorithm fitness function is carried out by performing various numerical experiments to inspect how it affects the scrap efficiency, allocation characteristics, and time consumption, targeting the nesting results of ship parts. This paper specifically concentrates on a method to minimize the scrap ratio and efficiently use the well-defined remnants of a raw plate after the nesting process for the remnant nesting. Therefore, experiments for various ship parts are carried out with the weighting factor method, one of the multi-objective optimum design methods. Using various weighting factor sets, the nesting results are evaluated in accordance with the above purposes and compared with each set for each ship part groups. Consequently, it is suggested that the nesting algorithm fitness function should be constructed differently depending on the characteristics of the parts and the needs of the users.

Optimization of Fuzzy Systems by Means of GA and Weighting Factor (유전자 알고리즘과 하중값을 이용한 퍼지 시스템의 최적화)

  • Park, Byoung-Jun;Oh, Sung-Kwun;Ahn, Tae-Chon;Kim, Hyun-Ki
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.6
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    • pp.789-799
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    • 1999
  • In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

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FUZZY IDENTIFICATION BY MEANS OF AUTO-TUNING ALGORITHM AND WEIGHTING FACTOR

  • Park, Chun-Seong;Oh, Sung-Kwun;Ahn, Tae-Chon;Pedrycz, Witold
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.701-706
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    • 1998
  • A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

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Uncertainty of Efficiency Equation of Solar Thermal Collectors (태양열 집열기 효율식의 불확도)

  • Lee, Kyoung-Ho;Lee, Soon-Myung
    • 한국신재생에너지학회:학술대회논문집
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    • pp.65.1-65.1
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    • 2010
  • Thermal performance tests of solar thermal collectors include determination of coefficient parameters in an efficiency equation. The parameters can be estimated using regression method to minimize an objective function as sum of differences between measured efficiency data and regressed efficiency equation. However, this conventional approach doesn't consider measurement uncertainties. In this presentation, a method to determine regression parameters in the efficiency equation and uncertainties of the parameters is described with mainly mathematical expressions based on literature reviews. In the method, parameters in the equation for collector efficiency can be determined using regression analysis with a weighting factor in the objective function. The weighting factor can be uncertainties of the differences between measured and fitted efficiencies. To evaluate the approach, performance estimation of a solar collector using the efficiency equation with uncertainties is compared to the result using the conventional efficiency equation by a simulated way for a case in one of previous studies.

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Study on semi-supervised local constant regression estimation

  • Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.3
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    • pp.579-585
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    • 2012
  • Many different semi-supervised learning algorithms have been proposed for use wit unlabeled data. However, most of them focus on classification problems. In this paper we propose a semi-supervised regression algorithm called the semi-supervised local constant estimator (SSLCE), based on the local constant estimator (LCE), and reveal the asymptotic properties of SSLCE. We also show that the SSLCE has a faster convergence rate than that of the LCE when a well chosen weighting factor is employed. Our experiment with synthetic data shows that the SSLCE can improve performance with unlabeled data, and we recommend its use with the proper size of unlabeled data.

Extremely Low Numerical Dispersion FDTD Method Based on H(2, 4) Scheme for Lossy Material

  • Oh, Il-Young;Hong, Yongjun;Yook, Jong-Gwan
    • Journal of electromagnetic engineering and science
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    • v.13 no.3
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    • pp.158-164
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    • 2013
  • This paper expands a previously proposed optimized higher order (2, 4) finite-difference time-domain scheme (H(2, 4) scheme) for use with lossy material. A low dispersion error is obtained by introducing a weighting factor and two scaling factors. The weighting factor creates isotropic dispersion, and the two scaling factors dramatically reduce the numerical dispersion error at an operating frequency. In addition, the results confirm that the proposed scheme performs better than the H(2, 4) scheme for wideband analysis. Lastly, the validity of the proposed scheme is verified by calculating a scattering problem of a lossy circular dielectric cylinder.

Shape Optimization of A Surface Roughened by Staggered Ribs To Enhance Turbulent Heat Transfer

  • Kim Hong-Min;Kim Kwang-Yong
    • 한국전산유체공학회:학술대회논문집
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    • pp.237-239
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    • 2003
  • The present study investigates on design optimization of rib-roughened two-dimensional channel to enhance turbulent heat transfer. Response surface method with Reynolds-averaged Navier-Stokes analysis is used as an optimization technique. Standard $k-{\varepsilon}$model with wall functions is adopted as a turbulence closure. The objective function is defined as a linear combination of heat transfer and friction drag coefficients with weighting factor. Computational results for overall heat transfer rate show good agreements with experimental data. Four design variables are optimized for weighting factor of 0.02.

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A Generalized Least Square Method using Dead Zone (불감대를 사용한 최소자승법의 일반화)

  • 이하정;최종호
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.10
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    • pp.727-732
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    • 1988
  • In this paper, a parameter estimation method of linear systems with bounded output disturbances is studied. The bound of the disturbances is assumed to known Weighting factors are proposed to modify LS(Least Square) algorithm in the parameter estimation method. The conditions of weighting factors are given so that the estimation method has good convergence properties. This condition is more relaxed form than other known conditions. The compensation term in the estimation equations is represented by a function of the output prediction error and this function should lie in a specified region on x-y plane to satisfy these conditions of weighting factors. A set of weighting factor is selected and an algorithm is proposed using this set of weighting factor. The proposed algorithm is compared with another existing algorithm by simulation and its performance in parameter estimation id discussed.

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Optimized LCL filter Design Method of Utility Interactive Inverter (계통연계형 인버터의 LCL필터 최적 설계기법)

  • Jung, Sang-Hyuk;Choi, Se-Wan
    • The Transactions of the Korean Institute of Power Electronics
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    • v.18 no.1
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    • pp.103-109
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    • 2013
  • The conventional LCL filter design method of the utility interactive inverter considers only harmonics attenuation of the current injected to the grid. However, in case of utility-interactive inverter with critical load the voltage quality of the critical load should also be considered for LCL filter design. Also, considering cost and volume of LCL filters. it is important to have minimum values of inductance and capacitance as far as the harmonic standards are satisfied. In this paper a LCL filter design method is proposed to satisfy not only the harmonic standards of the grid current during the grid-connected mode but the voltage quality of the critical load during grid-connected mode and stand-alone mode. With the proposed method optimized values of LCL filters could be obtained by applying weighting factor to voltage ripple across the critical load, inductor volume, amount of reactive current and system bandwidth.