• 제목/요약/키워드: Parameter, Weight

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위치에너지를 축적하는 태양동력 장기체공 무인기의 설계 인자 분석 (Design Parameter Analysis of a Solar-Powered, Potential Energy-Storing, Long Endurance UAV)

  • 양인영;이보화;장병희
    • 한국항공우주학회지
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    • 제39권10호
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    • pp.927-934
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    • 2011
  • 상승 비행에 의해 위치에너지를 축적하는 태양동력 장기체공 무인기에 대하여 설계 인자 분석을 수행하였다. 위치에너지 축적을 위한 비행과 관련된 인자인 최저 및 최고 수평 비행 고도, 활강 및 상승 각도, 설계점 속도 및 고도, 활강 및 상승 시작 시각을 분석 대상으로 하였다. 태양동력 무인기 구성품의 중량 모델을 이용하여 항공기 크기 및 중량을 결정하고 비행 중 생산 및 소모하는 에너지를 계산함으로써 임무 수행에 필요한 배터리 용량을 결정하였다. 각 설계 인자값과 무인기 중량의 관계를 연구하였다. 최고 수평 비행 고도, 활강 및 상승 각도, 설계점 속도 및 고도, 활강 및 상승 시작 시각에는 설계가 가능하도록하는 범위가 존재하며 이 범위 내에서 총 중량을 최소화하는 최적값이 존재하였다.

적응적 정규화, 프루닝 및 BIC를 이용한 신경망 최적화 방법 (An Optimization Method of Neural Networks using Adaptive Regulraization, Pruning, and BIC)

  • 이현진;박혜영
    • 한국멀티미디어학회논문지
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    • 제6권1호
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    • pp.136-147
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    • 2003
  • 주어진 문제에 대하여 최적의 성능을 가지는 신경회로망을 얻기 위해서는 학습을 통한 매개변수의 최적화 (parameter optimization)와 모델 선택을 통한 구조 최적화(structure optimization )의 통합적인 과정이 필요하다. 본 논문에서는, 각 세부 방법들의 특성을 고려하여, 공통의 특성을 갖는 방법들을 결합함으로써 효율적이면서도 일반화 성능을 높이는 총체적인 신경회로망 최적화 방법을 제안한다. 먼저 다양한 오차 함수를 사용할 수 있는 자연 기울기 강하 학습에 적응적 정규화 방법을 도입함으로써 가중치 매개변수(weight parameter)들을 최적화한다. 그리고 이렇게 최적화된 매개변수(parameter)들에 자연 프루닝(natural pruning)을 적용하여 불필요한 요소들을 제저하여 최적화 된 구조를 생성한다. 반복적인 과정에 의하여 후보 모델들을 구성하고 베이시안 정보 기준(Bayesian Information Criterion: BIC )을 이 용하여 최적의 모델을 평가하여 선택하는 방법을 제안하였다. 벤치마크 데이터에 대한 실험을 통하여 제안하는 방법의 구조 최적화 능력과 일반화 성능의 우수성을 보였다.

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다구찌법을 이용한 소음저감용 ER 패널의 파라미터 설계 (Parameter Design of an ER Panel for Noise Reduction using Taguchi Method)

  • 윤영민;김재환;최승복
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 추계학술대회논문집
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    • pp.638-642
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    • 2003
  • This paper presents a parameter design of an Electrorheological(ER) panel for noise reduction using Taguchi method. Taguchi method is a robust design method that determines control parameters in the presence of noise effect. Host structure thickness, spacer thickness, base oil viscosity and the weight ratio of ER particles are chosen for the control factors. A test setup in an SAE J1400 facility is used to analyze the sound transmission loss. The sensitivity of each factor with signal-to-noise(S/N) ratio and analysis of variance are investigated. The analysis results show that the weight ratio of ER particle and base oil viscosity of the ER fluid mostly affects the noise reduction in the presence of electric field. Based on the Taguchi method, an optimal configuration was designed and comparison is made with experimental result fer the verification.

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설계변수 공차를 고려한 브러시리스 모터 출력밀도 최적설계 (Optimum Design of the Brushless Motor Considering Parameter Tolerance)

  • 손병욱;이주
    • 전기학회논문지
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    • 제59권9호
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    • pp.1600-1604
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    • 2010
  • This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

Robust Estimator of Location Parameter

  • Park, Dongryeon
    • Communications for Statistical Applications and Methods
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    • 제11권1호
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    • pp.153-160
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    • 2004
  • In recent years, the size of data set which we usually handle is enormous, so a lot of outliers could be included in data set. Therefore the robust procedures that automatically handle outliers become very importance issue. We consider the robust estimation problem of location parameter in the univariate case. In this paper, we propose a new method for defining robustness weights for the weighted mean based on the median distance of observations and compare its performance with several existing robust estimators by a simulation study. It turns out that the proposed method is very competitive.

Parameters study on lateral buckling of submarine PIP pipelines

  • Zhang, Xinhu;Duan, Menglan;Wang, Yingying;Li, Tongtong
    • Ocean Systems Engineering
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    • 제6권1호
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    • pp.99-115
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    • 2016
  • In meeting the technical needs for deepwater conditions and overcoming the shortfalls of single-layer pipes for deepwater applications, pipe-in-pipe (PIP) systems have been developed. While, for PIP pipelines directly laid on the seabed or with partial embedment, one of the primary service risks is lateral buckling. The critical axial force is a key factor governing the global lateral buckling response that has been paid much more attention. It is influenced by global imperfections, submerged weight, stiffness, pipe-soil interaction characteristics, et al. In this study, Finite Element Models for imperfect PIP systems are established on the basis of 3D beam element and tube-to-tube element in Abaqus. A parameter study was conducted to investigate the effects of these parameters on the critical axial force and post-buckling forms. These parameters include structural parameters such as imperfections, clearance, and bulkhead spacing, pipe/soil interaction parameter, for instance, axial and lateral friction properties between pipeline and seabed, and load parameter submerged weight. Python as a programming language is been used to realize parametric modeling in Abaqus. Some conclusions are obtained which can provide a guide for the design of PIP pipelines.

Evaluation of Multi-criteria Performances of the TOPMODEL Simulations in a Small Forest Catchment based on the Concept of Equifinality of the Multiple Parameter Sets

  • Choi, Hyung Tae;Kim, Kyongha;Jun, Jae-Hong;Yoo, Jae-Yun;Jeong, Yong-Ho
    • 한국산림과학회지
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    • 제95권5호
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    • pp.569-579
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    • 2006
  • This study focuses on the application of multi-criteria performance measures based on the concept of equifinality to the calibration of the rainfall-runoff model TOPMODEL in a small deciduous forest catchment. The performance of each parameter set was evaluated by six performance measures, individually, and each set was identified as a behavioral or non-behavioral parameter set by a given behavioral acceptance threshold. Many behavioral parameter sets were scattered throughout the parameter space, and the range of model behavior and the sensitivity for each parameter varied considerably between the different performance measures. Sensitivity was very high in some parameters, and varied depending on the kind of performance measure as well. Compatibilities of behavioral parameter sets between different performance measures also varied, and very few parameter sets were selected to be used in making god predictions for all performance measures. Since different behavioral parameter sets with different likelihood weights were obtained for each performance measure, the decision on which performance measure to be used may be very important to achieve the goal of study. Therefore, one or more suitable performance measures should be selected depending on the environment and the goal of a study, and this may lead to decrease model uncertainty.