• 제목/요약/키워드: Marquardt

검색결과 189건 처리시간 0.023초

자동 공중급유를 위한 적외선 영상기반 상대 항법 (Relative Navigation for Autonomous Aerial Refueling Using Infra-red based Vision Systems)

  • 윤형철;양유영;이현재
    • 한국항공우주학회지
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    • 제46권7호
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    • pp.557-566
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    • 2018
  • 본 논문에서는 항공기 자동 공중급유를 위해 영상기반 상대 항법 시스템을 구현한다. 급유기와 피급유기는 프로브-드로그 방식의 공중급유를 가정하며 상대항법은 피급유기가 드로그에 대한 상대정보를 획득하며 진행한다. 드로그로부터 상대정보를 획득하기 위해 드로그 형태를 규정하고 IR카메라를 이용한 영상처리를 진행한다. 영상처리를 통해 얻은 드로그의 정보로부터 Gaussian Least Squares Differential Correction(GLSDC) 및 Levenberg-Marquardt(LM)을 이용한 상대항법을 진행하고 시뮬레이션을 통해 두 알고리즘의 분석을 수행한다.

A new approach to working coil design for a high frequency full bridge series resonant inverter fitted contactless induction heater

  • Dhar, Sujit;Dutta, Biswajit;Ghoshroy, Debasmita;Roy, Debabrata;Sadhu, Pradip Kumar;Ganguly, Ankur;Sanyal, Amar Nath;Das, Soumya
    • Advances in Computational Design
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    • 제2권4호
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    • pp.283-291
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    • 2017
  • High frequency full bridge series resonant inverters have become increasingly popular among power supply designers. One of the most important parameter for a High Frequency Full Bridge Series Resonant Inverter is optimal coil design. The optimal coil designing procedure is not a easy task. This paper deals with the New Approach to Optimal Design Procedure for a Real-time High Frequency Full Bridge Series Resonant Inverter in Induction Heating Equipment devices. A new design to experimental modelling of the physical properties and a practical power input simulation process for the non-sinusoidal input waveform is accepted. The design sensitivity analysis with Levenberg-Marquardt technique is used for the optimal design process. The proposed technique is applied to an Induction Heating Equipment devices model and the result is verified by real-time experiment. The main advantages of this design technique is to achieve more accurate temperature control with a huge amount of power saving.

Improving CMD Areal Density Analysis: Algorithms and Strategies

  • Wilson, R.E.
    • Journal of Astronomy and Space Sciences
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    • 제31권2호
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    • pp.121-130
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    • 2014
  • Essential ideas, successes, and difficulties of Areal Density Analysis (ADA) for color-magnitude diagrams (CMD's) of resolved stellar populations are examined, with explanation of various algorithms and strategies for optimal performance. A CMD-generation program computes theoretical datasets with simulated observational error and a solution program inverts the problem by the method of Differential Corrections (DC) so as to compute parameter values from observed magnitudes and colors, with standard error estimates and correlation coefficients. ADA promises not only impersonal results, but also significant saving of labor, especially where a given dataset is analyzed with several evolution models. Observational errors and multiple star systems, along with various single star characteristics and phenomena, are modeled directly via the Functional Statistics Algorithm (FSA). Unlike Monte Carlo, FSA is not dependent on a random number generator. Discussions include difficulties and overall requirements, such as need for fast evolutionary computation and realization of goals within machine memory limits. Degradation of results due to influence of pixelization on derivatives, Initial Mass Function (IMF) quantization, IMF steepness, low Areal Densities ($\mathcal{A}$), and large variation in $\mathcal{A}$ are reduced or eliminated through a variety of schemes that are explained sufficiently for general application. The Levenberg-Marquardt and MMS algorithms for improvement of solution convergence are contained within the DC program. An example of convergence, which typically is very good, is shown in tabular form. A number of theoretical and practical solution issues are discussed, as are prospects for further development.

大學 統計學科의 役割 (The role of the department of statistics)

  • 백운붕
    • 응용통계연구
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    • 제7권1호
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    • pp.59-68
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    • 1994
  • 우리나라에는 전국적으로 70여개 대학에 통계학과가 설치되어 있다. 매년 이들 통계학과에는 40명 내지 80명씩의 학생들이 입학한다. 그러므로 많은 통계학과 출신이 매년 사회에 진출하고 있다는 것을 알 수 있다. 그런데도 통계학으로 사회에 봉사할 수 있는 기회를 제공하거나 통계전문가를 통계적 문제해결을 위하여 채용하겠다는 곳은 별로 없는 것이 사실이다. 이것은 통계학 교수는 있으되 통계학과 출신의 일할 곳이 없다는 것을 나타내고 있는 것이다. 대학원에서 통계학으로 학위를 취득해도 사정은 마찬가지이다. 통계학 교수직을 제외하고는 통계학자나 통계전문가가 일할 자리가 없다는 것이 우리의 실정인 것이다. 그렇다면 과연 통계학과가 사회에서 원하는 존재가치가 있는 학과인가\ulcorner 통계학과는 통계학자에게 교수직과 연구의 장소를 제공하여 주기 위해서만 존재하는 것인가\ulcorner 이것은 통계학과 소속의 교수 누구나가 다같이 숙고하고 논의하여 해결책을 강구해야 할 중대한 문제라고 생각한다. 이 논문은 이러한 문제에 대하여 논의한 것이다.

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인공신경망을 사용한 섬유금속적층판의 온도에 따른 유동응력에 대한 수치해석적 예측 (Numerical Prediction of Temperature-Dependent Flow Stress on Fiber Metal Laminate using Artificial Neural Network)

  • 박으뜸;이영헌;김정;강범수;송우진
    • 소성∙가공
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    • 제27권4호
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    • pp.227-235
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    • 2018
  • The flow stresses have been identified prior to a numerical simulation for predicting a deformation of materials using the experimental or analytical analysis. Recently, the flow stress models considering the temperature effect have been developed to reduce the number of experiments. Artificial neural network can provide a simple procedure for solving a problem from the analytical models. The objective of this paper is the prediction of flow stress on the fiber metal laminate using the artificial neural network. First, the training data were obtained by conducting the uniaxial tensile tests at the various temperature conditions. After, the artificial neural network has been trained by Levenberg-Marquardt method. The numerical results of the trained model were compared with the analytical models predicted at the previous study. It is noted that the artificial neural network can predict flow stress effectively as compared with the previously-proposed analytical models.

쌍곡선법을 이용한 계측 기반 연약지반 침하 거동 예측의 최적화 방안 (The Optimization of Hyperbolic Settlement Prediction Method with the Field Data for Preloading on the Soft Ground)

  • 추윤식;김준현;황세환;정충기
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2010년도 춘계 학술발표회
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    • pp.457-467
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    • 2010
  • The settlement prediction is very important to preloading method for a construction site on a soft ground. At the design stage, however, it is hard to predict the settlement exactly due to limitations of the site survey. Most of the settlement prediction is performed by a regression settlement curve based on the field data during a construction. In Korea, hyperbolic method has been most commonly used to align the settlement curve with the field data, because of its simplicity and many application cases. The results from hyperbolic method, however, may be differed by data selections or data fitting methods. In this study, the analyses using hyperbolic method were performed about the field data of $\bigcirc\bigcirc$ site in Pusan. Two data fitting methods, using an axis transformation or an alternative method, were applied with the various data group. If data was used only after the ground water level being stabilized, fitting results using both methods were in good agreement with the measured data. Without the information about the ground water level, the alternative method gives better results with the field data than the method using an axis transformation.

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Extraction of Passive Device Model Parameters Using Genetic Algorithms

  • Yun, Il-Gu;Carastro, Lawrence A.;Poddar, Ravi;Brooke, Martin A.;May, Gary S.;Hyun, Kyung-Sook;Pyun, Kwang-Eui
    • ETRI Journal
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    • 제22권1호
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    • pp.38-46
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    • 2000
  • The extraction of model parameters for embedded passive components is crucial for designing and characterizing the performance of multichip module (MCM) substrates. In this paper, a method for optimizing the extraction of these parameters using genetic algorithms is presented. The results of this method are compared with optimization using the Levenberg-Marquardt (LM) algorithm used in the HSPICE circuit modeling tool. A set of integrated resistor structures are fabricated, and their scattering parameters are measured for a range of frequencies from 45 MHz to 5 GHz. Optimal equivalent circuit models for these structures are derived from the s-parameter measurements using each algorithm. Predicted s-parameters for the optimized equivalent circuit are then obtained from HSPICE. The difference between the measured and predicted s-parameters in the frequency range of interest is used as a measure of the accuracy of the two optimization algorithms. It is determined that the LM method is extremely dependent upon the initial starting point of the parameter search and is thus prone to become trapped in local minima. This drawback is alleviated and the accuracy of the parameter values obtained is improved using genetic algorithms.

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안면부 황금 분할 마스크를 이용한 간편한 안면 윤곽 분석 (Easy Facial Analysis Using Facial Golden Mask)

  • 최찬;김용하
    • Archives of Plastic Surgery
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    • 제33권2호
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    • pp.168-174
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    • 2006
  • For over two thousand years, many artists and scientists have tried to understand or quantify the form of the perfect, ideal, or the most beautiful face both in art and in vivo(life). However, this mathematical relationship has been consistently and repeatedly reported to be present in beautiful things. This particular relationship is referred to as the golden ratio. It is a mathematical ratio of 1.618 : 1 that seems to appear recurrently in beautiful things in nature as well as in other things that are seen as beautiful. Dr. Marquardt made the facial golden mask that contains and includes all of the 1-dimensional and 2-dimensional geometric golden element formed from the golden ratio. The purpose of this study is to evaluate the usefulness of the golden facial mask. In our cases(n=40), the authors applied the facial golden mask to the preoperative and postoperative photographs, and scored each photograph. Compared with the average scores of the facial mask applied photographs and none applied photographs using non-parametric test, statistical significance was not checked (p > 0.05). It means that the facial golden mask can be used for facial analysis. The facial golden mask is easy to apply, cheap and relatively objective. So, the authors introduce the one of useful facial analyses.

추계학적 비선형 모형을 이용한 달천의 실시간 수질예측 (Real Time Water Quality Forecasting at Dalchun Using Nonlinear Stochastic Model)

  • 연인성;조용진;김건흥
    • 상하수도학회지
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    • 제19권6호
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    • pp.738-748
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    • 2005
  • Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.

공압식 능동형 엔진마운트시스템의 최적 제어매개변수 식별 (Identification of Optimal Control Parameters for a Pneumatic Active Engine Mount System)

  • 김일조;이재천;최재용;김정훈
    • 한국자동차공학회논문집
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    • 제20권2호
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    • pp.30-37
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    • 2012
  • Pneumatic Active Engine Mount(PAEM) with open-loop control system has been developed to reduce the transmission of the idle-shake vibration induced by engine effectively and economically. A solenoid valve installed between PAEM and vacuum tank is on-off switched by the Pulse Width Modulate(PWM) control signal to decrease the dynamic stiffness of the engine mount. This paper presents the methodology to identify the optimal values of control parameters of a PAEM, i.e, turn-on timing and duty ratio of PWM signal for 6 different idle driving conditions. A scanning algorithm was first applied to the vehicle test to obtain the approximate optimal control parameters minimizing the vibration at front seat rail and at steering wheel. Then the PAEM system identification was fulfilled to find accurate optimal control parameters by using multi-layer neural networks of Levenberg-Marquardt algorithm with vehicle test data.