• 제목/요약/키워드: Descent

검색결과 793건 처리시간 0.026초

자유낙하하는 판의 fluttering 특성 연구 (Fluttering Characteristics of Free-falling Plates)

  • 홍슬기;채석봉;김주하
    • 한국가시화정보학회지
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    • 제15권2호
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    • pp.33-40
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    • 2017
  • Abstract In the present study, the characteristics of kinematics and dynamics in the fluttering motion of free-falling plates are investigated at Reynolds number of $10^5$. We record quasi-two-dimensional trajectories of free-falling plates with and without superhydrophobic coating using high-speed camera, and compute the drag and lift forces by trajectory analysis. Translational and angular velocities are modeled as harmonic functions with specific phase differences. In particular, periodic mass elevations near turning points are explained using the suggested models. At each turning point, a sudden drop in lift and a rapid increase in drag occur simultaneously due to fast increase in angle of attack. However, the lift is increased over the buoyancy-corrected weight of plate during gliding flight, resulting in periodic mass elevations near turning points. Superhydrophobicity is shown to increase lift but to reduce drag on a fluttering plate, resulting in the decrease of mean descent speed.

학습 알고리듬을 이용한 자동변속기의 변속제어기 설계 (Design of shift controller using learning algorithm in automatic transmission)

  • 전윤식;장효환
    • 대한기계학회논문집A
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    • 제22권3호
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    • pp.663-670
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    • 1998
  • Most of feedback shift controllers developed in the past have fixed control parameters tuned by experts using a trial and error method. Therefore, those controllers cannot satisfy the best control performance under various driving conditions. To improve the shift quality under various driving conditions, a new self-organizing controller(SOC) that has an optimal control performance through self-learning of driving conditions and driver's pattern is designed in this study. The proposed SOC algorithm for the shift controller uses simple descent method and has less calculation time than complex fuzzy relation, thus makes real-time control passible. PCSV (Pressure Control Solenoid Valve) control current is used as a control input, and turbine speed of the torque converter is used indirectly to monitor the transient torque as a feedback signal, which is more convenient to use and economic than the torque signal measured directoly by a torque sensor. The results of computer simulations show that an apparent reduction of shift-transient torque is obtained through the process of each run without initial fuzzy rules and a good control performance in the shift-transient torque is also obtained.

로버스트 다층전방향 신경망을 이용한 패턴인식 (Pattern Recognition using Robust Feedforward Neural Networks)

  • 황창하;김상민
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.345-355
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    • 1998
  • 다층전방향 신경망을 학습시키기 위해 역전파 알고리즘이 널리 사용되고 있으나 이 알고리즘은 긴 훈련시간, 극소점 문제, 이상치에 민감하다는 단점을 가지고 있다. 한편 실제문제에서는 많은 경우에 자료에 과대오차와 이상치가 포함되게 된다. 따라서 과대 오차에 민감하지 않고, 이상치의 영향을 최소화시키는 로버스트 역전파 알고리즘의 필요성이 대두되었다. 본 논문에서는 기존의 두종류의 로버스트 역전파 알고리즘을 이론적으로 비교하고 비선형 회귀 함수추정과 문자인식과 같은 패턴인식 문제에 적용하여 실험결과를 분석한다. 그리고 향후 연구과제로 신경망 학습을 위해 베이지안 기법의 사용을 제안한다.

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광대역 전자파를 이용한 역산란 해석 연구 (Analysis of Microwave Inverse Scattering Using the Broadband Electromagnetic waves)

  • 이정훈;정용식
    • 한국전자파학회:학술대회논문집
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    • 한국전자파학회 2005년도 종합학술발표회 논문집 Vol.15 No.1
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    • pp.169-174
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    • 2005
  • 본 논문에서는 시간영역 유한차분법(FDTD: Finite-Difference Time-Domain Method)과 설계민감도법(Design Sensitivity Analysis)을 이용하여 유전체 산란체(Dielectric Scatterer)를 복원하기 위한 역산란문제(Inverse Scattering의 새로운 해석기법을 제안하였다. 이때 복원의 빠른 수렴을 위하여 도함수를 이용한 설계민감도법을 도입하였고 본 연구에서는 시간영역 유한차분법으로부터 직접 설계민감도 수식을 도출하였다. 계산의 효율성을 위하여 보조변수법(Adjoint Variable Method)을 도입하여 보조변수 방정식을 도출하고 최적화 알고리듬으로 최대경사도법을 이용하여 반복적인 추정을 통하여 유전체를 복원하였다. 본 연구의 타당성의 보이기 위하여 2차원 $TM^2$에서의 유전체 복원 사례를 제시한다.

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통합적 인공지능 기법을 이용한 결함인식 (Crack Identification Based on Synthetic Artificial Intelligent Technique)

  • 심문보;서명원
    • 대한기계학회논문집A
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    • 제25권12호
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    • pp.2062-2069
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    • 2001
  • It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

통합적 인공지능 기법을 이용한 결함인식 (Crack identification based on synthetic artificial intelligent technique)

  • 심문보;서명원
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집C
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    • pp.182-188
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    • 2001
  • It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

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Resource allocation in downlink SWIPT-based cooperative NOMA systems

  • Wang, Longqi;Xu, Ding
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권1호
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    • pp.20-39
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    • 2020
  • This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.

확률론적 의사결정기법을 이용한 태양광 발전 시스템의 고장검출 알고리즘 (Fault Detection Algorithm of Photovoltaic Power Systems using Stochastic Decision Making Approach)

  • 조현철;이관호
    • 융합신호처리학회논문지
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    • 제12권3호
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    • pp.212-216
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    • 2011
  • 태양광 발전 시스템의 고장검출은 고장으로 인해 발생되는 기술적 및 경제적 손실을 최대한 줄이기 위한 첨단 기술로 각광을 받고 있다. 본 논문은 푸리에 신경회로망과 확률론적 의사결정법을 이용한 태양광 발전 시스템의 새로운 고장진단 알고리즘을 제안한다. 우선 태양광 시스템의 동적 모델링을 위하여 최급강하 기반 최적화 기법을 통해 신경회로망 모델을 구성하며 GLRT 알고리즘을 이용하여 태양광 시스템의 확률론적 고장검출 기법을 제안한다. 제안한 고장검출 알고리즘의 타당성 검증을 위하여 태양광 고장검출 테스트베드를 제작하여 실시간 실험을 실시하였으며 이 때 태양광으로부터의 신호는 직류 전력선 통신을 이용하였다.

Optimization of Hydroxyl Radical Scavenging Activity of Exopolysaccharides from Inonotus obliquus in Submerged Fermentation Using Response Surface Methodology

  • Chen, Hui;Xu, Xiangqun;Zhu, Yang
    • Journal of Microbiology and Biotechnology
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    • 제20권4호
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    • pp.835-843
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    • 2010
  • The objectives of this study were to investigate the effect of fermentation medium on the hydroxyl radical scavenging activity of exopolysaccharides from Inonotus obliquus by response surface methodology (RSM). A two-level fractional factorial design was used to evaluate the effect of different components of the medium. Corn flour, peptone, and $KH_2PO_4$ were important factors significantly affecting hydroxyl radical scavenging activity. These selected variables were subsequently optimized using path of steepest ascent (descent), a central composite design, and response surface analysis. The optimal medium composition was (% w/v): corn flour 5.30, peptone 0.32, $KH_2PO_4$ 0.26, $MgSO_4$ 0.02, and $CaCl_2$ 0.01. Under the optimal condition, the hydroxyl radical scavenging rate (49.4%) was much higher than that using either basal fermentation medium (10.2%) and single variable optimization of fermentation medium (35.5%). The main monosaccharides components of the RSM optimized polysaccharides are rhamnose, arabinose, xylose, mannose, glucose, and galactose with molar proportion at 1.45%, 3.63%, 2.17%, 15.94%, 50.00%, and 26.81%.

등가정하중을 이용한 구조최적설계 방법을 이용한 비선형 거동구조물의 최적설계 (Non-linear Structural Optimization Using NROESL)

  • 박기종;박경진
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.1256-1261
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    • 2004
  • Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is proposed to perform optimization of non-linear response structures. It is more expensive to carry out nonlinear response optimization than linear response optimization. The conventional method spends most of the total design time on nonlinear analysis. Thus, the NROESL algorithm makes the equivalent static load cases for each response and repeatedly performs linear response optimization and uses them as multiple loading conditions. The equivalent static loads are defined as the loads in the linear analysis, which generates the same response field as those in non-linear analysis. The algorithm is validated for the convergence and the optimality. The function satisfies the descent condition at each cycle and the NROESL algorithm converges. It is mathematically validated that the solution of the algorithm satisfies the Karush-Kuhn-Tucker necessary condition of the original nonlinear response optimization problem. The NROESL algorithm is applied to two structural problems. Conventional optimization with sensitivity analysis using the finite difference method is also applied to the same examples. The results of the optimizations are compared. The proposed method is very efficient and derives good solutions.

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