• Composites Research
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• v.31 no.5
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• pp.177-185
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• 2018

Fiber metal laminate (FML) is a type of hybrid composites which consist of metallic and fiber-reinforced plastic sheets. As the FML has a drawback of the delamination that is a failure of the interfacial adhesive layer, the nominal stresses and the energy release rates should be determined to identify the delamination behavior. However, it is difficult to derive the nominal stresses and the energy release rates since the operating temperature of the equipment is restricted. For this reason, the objective of this paper is to predict the mode-I nominal stress and the mode-I energy release rate of the adhesive layer using the inverse analysis based on the Levenberg-Marquardt method. First, the mode-I nominal stress was assumed as the tensile strength of the adhesive layer, and the mode-I energy release rate was obtained from the double cantilever beam test. Next, the finite element method was applied to predict the mode-I delamination behavior. Finally, the mode-I nominal stress and the mode-I energy release rate were predicted by the inverse analysis. In addition, the convergence of the parameters was validated by trying to input two cases of the initial parameters. Consequently, it is noted that the inverse analysis can predict the mode-I delamination behavior, and the two input parameters were converged to similar values.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.8
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• pp.803-808
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• 2003

Several dielectric pipes buried in the lossy half space are reconstructed from the scattered fields measured along the interface between the air and the lossy ground. Iterative inversion method by using the hybrid optimization algorithm combining the genetic and the Levenberg-Marquardt algorithm enables us to find the positions, the sizes, and the medium parameters such as the permittivities and the conductivities of the buried pipes as well as those of the background lossy half space even when the dielectric pipes are close together. Illposedness of the inversion caused by the errors in the measured scattered fields are regularized by filtering the evanescent modes of the scattered fields out.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.195-201
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• 2019

The logarithmic objective function used in waveform inversion minimizes the logarithmic differences between the observed and modeled data. Laplace-domain waveform inversions usually adopt the logarithmic objective function and the diagonal elements of the pseudo-Hessian for optimization. In this case, we apply the Levenberg-Marquardt algorithm to prevent the diagonal elements of the pseudo-Hessian from being zero or near-zero values. In this study, we analyzed the diagonal elements of the pseudo-Hessian of the logarithmic objective function and showed that there is no zero or near-zero value in the diagonal elements of the pseudo-Hessian for acoustic waveform inversion in the Laplace domain. Accordingly, we do not need to apply the Levenberg-Marquardt algorithm when we regularize the gradient direction using the pseudo-Hessian of the logarithmic objective function. Numerical examples using synthetic and field datasets demonstrate that we can obtain inversion results without applying the Levenberg-Marquardt method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.2
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• pp.115-124
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• 2003

In this paper, the effects of vehicle loads on flat slab system are investigated on the basis of the previous studies for beam-gilder parking structural system. The influence surfaces of flat slab for a typical design section are constructed lot the purpose of obtaining maximum member forces under vehicle loads. In addition, the equivalent vehicle load factors for flat slab parking structures are suggested using artificial neural network. The network responses we compared with the results obtained by numerical analyses to verify the validation of Levenberg-Marquardt algorithm adopted as training method in this Paper. Many parameter studies for the flat slab structural system show dominant vehicle load effects at the center positive moments in both column and middle strips, like the beam-girder parking structural system.

• Journal of Integrative Natural Science
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• v.1 no.3
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• pp.221-229
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• 2008

본 논문에서는 기존의 개인 식별 방법의 한계를 해결하는 대안으로 떠오르고 있는 생체인식 기술 중 인식률이 뛰어나고 신뢰성 있는 홍채인식 시스템을 구현하고자 한다. 구현을 위하여 신호처리 분야에서 주로 사용되는 wavelet변환으로 계수 특징 값 추출을 하였으며, 인식률을 알아보기 위하여 신경망 기법을 이용하고자 한다. 그러나 신경망 기법에서 주로 사용되는 비선형 최적화기법인 Scale Conjugate Gradient는 최적화 문제점을 해결하기에는 수렴속도가 느리기 때문에 적합하지 않다. 따라서 본 논문에서는 기존 Scale Conjugate Gradient를 보완한 Levenberg-Marquardt Back-Propagation을 홍채인식에 적용하여 구현함으로써 인식율을 높이고자 한다. 적용한 알고리즘 구현으로 해의 수렴정도, 변수 벡터의 변화정도에 따라 크기를 적절히 변화시킴으로써 수렴속도를 개선하고, 효율성과 안정성을 동시에 얻을 수 있었다.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.634-639
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• 2012

In this paper, we propose nonlinear optimization method for feature matching from multiple view image. Typical solution of feature matching is by solving linear equation. However this solution has large error due to nonlinearity of image formation model. If typical nonlinear optimization method is used, complexity grows exponentially over the number of features. To make complexity lower, we use sparse Levenberg-Marquardt nonlinear optimization for matching of features over multiple view image.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.70-70
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• 2001

인공위성영상(ETM+)을 이용하여 산불피해지역을 추출하기 위해 신경망기법을 응용하였다. 적용된 신경망은 3개의 층으로 구성된 전향신경망이며 Levenberg-Marquardt 역전파 훈련 알고리즘을 사용하였다. 산불피해지역은 심, 중, 경 세 가지로 나누었으며, 그외 피해없는 산림지역과 기타(나지, 도시 등)지역으로 분류하였다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.6
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• pp.939-945
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• 2000

A cylindrical object buried in the lossy half space is reconstructed from the measured scattered fields above the lossy half space. The position, the size and the medium parameters i.e. relative dielectric constants and conductivity of the buried object as well as the medium parameters of the background lossy half space are obtained from the scattered fields by using the iterative inversion method and the optimization hybrid algorithm combining the genetic algorithm and the Levenberg-Marquardt algorithm. Illposedness of the inversion due to the measurement errors in the scattered fields are regularized by filtering out the evanescent modes in the spatial frequency spectrum domain.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.803-810
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• 2003

In this paper, we describe a fast image mosaic method for constructing a large-scale image with video image captured from cameras that are arranged in radial shape. In the first step, we adopt the phase correlation algorithm to estimate the horizontal and vertical displacement between two adjacent images. Secondly, we calculate the accurate transform matrix among those cameras with Levenberg-Marquardt method. In the last step, those images are stitched into one large scale image in real-time by applying the transform matrix to the texture mapping function of DirectX. The feature of the method is that we do not need to use special hardware devices or write machine-level programs for Implementing a real-time mosaic system since we use conventional graphic APIs (Application Programming Interfaces), DirectX for image synthesis process.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.625-627
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• 2002

본 논문에서는 의료영상 인식 기술 중 인식률이 뛰어나고 신뢰성 있는 대뇌출혈성 병변인식 시스템을 구현하기 위하여 신호처리 분야에서 주로 사용되는 Wavelet 변환과 신경망 기법을 이용하고자 한다. 그러나 신경망 기법에서 주로 사용되는 비선형 최적화기법인 Gradient descent BP는 최적화 문제점을 해결하기에는 수렴속도가 느리기 때문에 적합하지 않다. 따라서 본 논문에서는 기존 Gradient descent BP를 보완한 Levenberg-Marquardt Back-Propagation을 대뇌출혈성 병변인식에 적용하여 구현함으로써 총 50개의 패턴 중 45개의 영상이 인식에 성공하였고 전체 평균 인식률은 각각 90%와 87%의 인식률을 보였다.