• Title/Summary/Keyword: Parameter, Weight

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

  • Yang, In-Young;Lee, Bo-Hwa;Chang, Byung-Hee
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.10
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    • pp.927-934
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    • 2011
  • Design parameter analysis is performed for a solar-powered UAV, storing potential energy by climb flight. Parameters related to the flight for saving potential energy, i.e. minimum & maximum altitudes for level flight, gliding & climbing angle, design point speed & altitude, gliding & climbing start time are investigated as design parameters. Weight and size of the UAV are determined using a weight model for the components of the solar-powered UAVs. Produced energy and consumed energy are calculated using these weight and size, yielding the required weight of the battery for a given mission. Relationship between the total weight of the UAV and each parameter is investigated. For the parameters listed above, there exist their ranges only where the design is possible. And there exist optimal values of these parameters minimizing the total weight.

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

  • 이현진;박혜영
    • Journal of Korea Multimedia Society
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    • v.6 no.1
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    • pp.136-147
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    • 2003
  • To achieve an optimal performance for a given problem, we need an integrative process of the parameter optimization via learning and the structure optimization via model selection. In this paper, we propose an efficient optimization method for improving generalization performance by considering the property of each sub-method and by combining them with common theoretical properties. First, weight parameters are optimized by natural gradient teaming with adaptive regularization, which uses a diverse error function. Second, the network structure is optimized by eliminating unnecessary parameters with natural pruning. Through iterating these processes, candidate models are constructed and evaluated based on the Bayesian Information Criterion so that an optimal one is finally selected. Through computational experiments on benchmark problems, we confirm the weight parameter and structure optimization performance of the proposed method.

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

  • 윤영민;김재환;최승복
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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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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Optimum Design of the Brushless Motor Considering Parameter Tolerance (설계변수 공차를 고려한 브러시리스 모터 출력밀도 최적설계)

  • Son, Byoung-Ook;Lee, Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.9
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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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    • v.11 no.1
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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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    • v.6 no.1
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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
    • Journal of Korean Society of Forest Science
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    • v.95 no.5
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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.