• Title/Summary/Keyword: near-optimal parameter

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An intelligent semi-active isolation system based on ground motion characteristic prediction

  • Lin, Tzu-Kang;Lu, Lyan-Ywan;Hsiao, Chia-En;Lee, Dong-You
    • Earthquakes and Structures
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    • v.22 no.1
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    • pp.53-64
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    • 2022
  • This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.

Development of the Algorithm for Optimizing Wavelength Selection in Multiple Linear Regression

  • Hoeil Chung
    • Near Infrared Analysis
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    • v.1 no.1
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    • pp.1-7
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    • 2000
  • A convenient algorithm for optimizing wavelength selection in multiple linear regression (MLR) has been developed. MOP (MLP Optimization Program) has been developed to test all possible MLR calibration models in a given spectral range and finally find an optimal MLR model with external validation capability. MOP generates all calibration models from all possible combinations of wavelength, and simultaneously calculates SEC (Standard Error of Calibration) and SEV (Standard Error of Validation) by predicting samples in a validation data set. Finally, with determined SEC and SEV, it calculates another parameter called SAD (Sum of SEC, SEV, and Absolute Difference between SEC and SEV: sum(SEC+SEV+Abs(SEC-SEV)). SAD is an useful parameter to find an optimal calibration model without over-fitting by simultaneously evaluating SEC, SEV, and difference of error between calibration and validation. The calibration model corresponding to the smallest SAD value is chosen as an optimum because the errors in both calibration and validation are minimal as well as similar in scale. To evaluate the capability of MOP, the determination of benzene content in unleaded gasoline has been examined. MOP successfully found the optimal calibration model and showed the better calibration and independent prediction performance compared to conventional MLR calibration.

Determination of optimal Conditions for a Gas Metal Arc Wending Process Using the Genetic Algorithm

  • Kim, D.;Rhee, S.
    • International Journal of Korean Welding Society
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    • v.1 no.1
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    • pp.44-50
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    • 2001
  • A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

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A V­Groove $CO_2$ Gas Metal Arc Welding Process with Root Face Height Using Genetic Algorithm

  • Ahn, S.;Rhee, S.
    • International Journal of Korean Welding Society
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    • v.3 no.2
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    • pp.15-23
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    • 2003
  • A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

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Determination on Optima Condition for a Gas Metal Arc Welding Process Using Genetic Algorithm (유전 알고리즘을 이용한 가스 메탈 아크 용접 공정의 최적 조건 설정에 관한 연구)

  • 김동철;이세헌
    • Journal of Welding and Joining
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    • v.18 no.5
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    • pp.63-69
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    • 2000
  • A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

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Optimal Blank Design for Sheet Metal Stamping (박판성형공정의 블랭크 최적설계)

  • 김용환
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2000.04a
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    • pp.141-145
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    • 2000
  • A systematic method to find the optimal blank shape for sheet forming is proposed by coupling the numerical simulation technique. A weighted parameter was introduced in order to simplify the multi-variable optimization problem to a single-variable problem. The proposed method has been applied to the blank design of drawing processes to obtain the near-net shape within the required error bound after forming, Excellent results have been obtained between the numerical results and the target contour shapes. Through the investigation the proposed systematic method for optimal blank design is found to be effective in the practical forming processes

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Multi-Time Scale Separations and Optimal Control Problems of Multi-Parameter Singular Perturbation Systems (여러 매개상수 특이접동계에서의 여러 시간스케일 분리와 최적제어 문제)

  • Kim, Sam-Soo;Hong, Jae-Keun;Kim, Soo-Joong
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.1
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    • pp.20-27
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    • 1987
  • The hierarchical approach method is proposed to sperate each different time scale sub-systems from linear time invariant multi-parameter singular perturbation systems. By means of this proposal, the original multi-parameter singular perturbation systems is completely separated into independent subsystems with each different time scale. It is also investigated that the controllability of the system is invariant. And this paper applies singular perturbation methods to the minimum control effort problem for linear time invariant systems with constrained controls. Also near-optimum control theory, which is based on dividing the total time interval with the time scales respectively, is proposed. As a result, the time scale separation method is show to be particularly useful in a near optimum design which can be otained through a decentralized control structure.

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Torque shaping for near-minimum-time optimal slewing of 3-axis spacecraft (3축 위성체의 준최소시간 선회기동을 위한 입력형상최적화)

  • 김기석;김희섭;김유단
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1330-1333
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    • 1997
  • In this paper, the optimal torque shaping is obtained for 3-axis rotation of a spacecraft. The true optimal 3-axis rotation of rigid spaeraft is first investigated via parameter optimization method with prescribed switching times. Input torque shape of the troque generating device mounted on the central hub is optimized using fourier Series expansion so that the spacecraft may slew while minimizing the vibration energy of flexible modes. Numerical results show that proposed method suggests a reference trahectory for open-loop control, and also verify that it can minimize the vibratory modes of the spacecraft during/after the rest-to-rest maneuver.

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Dynamic Optimal Design of Continuous Beams (연속보의 동적 최적설계에 관한 연구)

  • 이병구;오상진;모정만
    • Computational Structural Engineering
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    • v.10 no.2
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    • pp.233-242
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    • 1997
  • The main purpose of this paper is to investigate the dynamic optimal design of continuous beams. The computer-aided optimization technique is used to obtain the near-optimal parameters of continuous beam. The computer program is developed to obtain the natural frequency parameters and the forced vibration responses to a transit point load for the continuous beam with variable support spacing, mass and stiffness. The model test data is in good agreement with the computer calculation, which serves to validate the mathematical analysis. The optimization function to describe the design efficiency is defined as a linear combination of four dimensionless span characteristics; the maximum dynamic stress; the stress difference between span segments; the rms deflection under the transit point load; and the total span mass. Studies of three span beams show that the beam with near-optimal parameters can improve design efficiency when compared to a uniform beam with even spacing of the same total span length.

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Optimal Parameter Selection of Near-Infrared Optics Based Design of Experiment for Silicon Wafer in Solar Cell (태양전지 실리콘 웨이퍼를 위한 실험계획법 기반 근적외선 광학계의 최적조건 선정)

  • Seo, Hyoung Jun;Kim, Gyung Bum
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.3
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    • pp.29-34
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    • 2013
  • Solar cell has been considered as renewable green energy. Its silicon wafer thickness is thinner due to manufacturing cost and accordingly micro cracks is often generated in the process. Micro cracks result in bad quality of solar cell, and so their accurate and reliable detection is required. In this paper, near-infrared optics system is newly designed based on the analysis of near-infrared transmittance characteristics and its important parameters are optimally selected using the design of experiment for micro crack detection in solar cell wafer. The performance of the proposed method is verified using several experiments.