• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(1)
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• pp.173-176
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• 2001

Several dielectric as well as conducting cylinders 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 cylinders as well as those of the background lossy half space. 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.105-107
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• 2006

As internet streaming data increase, transport protocol such as TCP, TGP-Friendly is important to study control transmission rate and share of Internet bandwidth. In this paper, we propose a TCP-Friendly protocol using Neural Network for media delivery over wired Internet which has various traffic size(PTFRC). PTFRC can effectively send streaming data when occur congestion and predict one-step ahead round trip time and packet loss rate. A multi-layer perceptron structure is used as the prediction model, and the Levenberg-Marquardt algorithm is used as a traning algorithm. The performance of the PTFRC was evaluated by the share of Bandwidth and packet loss rate with various protocols.

• 한국정밀공학회지
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• 제18권11호
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• pp.124-131
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• 2001

Fault diagnosis of an assembled small motor relies usually on human experts hearing ability. The quality of diagnosis depends, however, heavily on physical conditions of the human experts. A fault diagnosis system for assembled small motors is developed using artificial neural network (ANN) in this paper. It is consisted of sound sampling device and fault diagnosis software package. Six parameters are defined to characterize the sampled sound waves. The Levenberg-Marquardt Backpropagation (LMBP) Algorithm is used to diagnose the fault of assembled small motors. Experimental results for more than two hundred small motors verify the performance of the developed system.

• Journal of Advanced Marine Engineering and Technology
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• 제23권5호
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• pp.637-653
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• 1999

In this study well-known burned rate expressions of Weibe function and double Wiebe function have been adopted for the combustion analysis of large two stroke marine diesel engine. A cycle simulation program was also developed to predict the performance and pressure waves in pipes using validated burned rate function,. Levenberg-Marquardt iteration method was applied to cali-brate the shape coefficients included in double Wiebe function for the performance prediction of two-stroke marine diesel engine. As a result the performance prediction using double Wiebe func-tion is well correlated withexperimental dta with the accuracy of 5% and pressure waves in intake and transport pipe are well predicted. From the results of this study it can be confirmed that the shape coefficients of burned rate function should be modified using the numerical method suggested for the accurated prediction and double Wiebe function is more suitable than Wiebe func-tion for combustion analysis of large two stroke marine engine.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.297-301
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• 2005

In this paper, we propose a method to estimate camera motion parameter based on invariant point features. Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time. The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum. In order to complement these shortfalls, we, first propose constructing feature models using invariant vector of geometry. Secondly, we propose a two-stage calculation method to improve accuracy and convergence by using homography and LM method. In the experiment, we compare and analyze the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.233-240
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• 2002

In this paper, the effects of vehicle loads on flat slab system are investigated on the basis of the previous studies for beam-girder parking structural system. The influence surfaces of flat slab for typical design section are developed for 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 are compared with the results by numerical analyses to verify the validation of Levenberg-Marquardt algorithm adopted as training method in this paper. Many parameter studies fur 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.

• 한국정보통신학회논문지
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• 제4권1호
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• pp.131-138
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• 2000

This paper works on development of an algorithm for mapping of cerebral perfusion parameters using the gamma-variate curve fitting. The signal intensity variate curve according to time measured in each pixel of perfusion MRI is nonlinear, and various hemodynamic parameters are not computed accurately. Levenberg-Marquardt algorithm(LMA), nonlinear optimum algorithm with high convergent speed and stability, is used to compute them. That is, the signal intensity variate curve is fitted by the gamma-variate function. Various hemodynamic parameters - Cerebral Blood Volume(C.B.V), Mean Transit Time(M.T.T), Cerebral Blood Flow(C.B.F), Time-to-Peak(T.T.P), Bolus Arrival Time(B.A.T), Maximum Slope(M.S) - are computed using LMA.

• 대한기계학회논문집B
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• 제30권3호
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• pp.270-277
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• 2006

Inverse radiation problems were solved for estimating boundary temperature distribution in a way of function estimation approach in an axisymmetric absorbing, emitting and scattering medium, given the measured radiative data. In order to reduce the computational time fur the calculation of sensitivity matrix, automatic differentiation and Broyden combined method were adopted, and their computational precision and efficiency were compared with the result obtained by finite difference approximation.. In inverse analysis, the effects of the precision of sensitivity matrix, the number of measurement points and measurement error on the estimation accuracy had been inspected using quasi-Newton method as an inverse method. Inverse solutions were validated with the result acquired by additional inverse methods of conjugate-gradient method or Levenberg-Marquardt method.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.77-88
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• 2021

Heart Failure represents a critical pathological case that is challenging to predict and discover at an early age, with a notable increase in morbidity and mortality. Machine Learning and Neural Network techniques play a crucial role in predicting heart attacks, diseases and more. These techniques give valuable perspectives for clinicians who may then adjust their diagnosis for each individual patient. This paper evaluated neural network models for heart attacks predictions. Several online learning methods were investigated to automatically and accurately predict heart attacks. The UCI dataset was used in this work to train and evaluate First Order and Second Order Online Learning methods; namely Backpropagation, Delta bar Delta, Levenberg Marquardt and QuickProp learning methods. An optimizer technique was also used to minimize the random noise in the database. A regularization concept was employed to further improve the generalization of the model. Results show that a three layers' NN model with a Backpropagation algorithm and Nadam optimizer achieved a promising accuracy for the heart attach prediction tasks.

• Coupled systems mechanics
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• 제12권5호
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• pp.419-428
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• 2023

We have developed a model for estimating the parameters of viscous materials from indirect tensile tests for asphalt. This is a simple Burger nonlinear rheological two-cell model or standard model. At the same time, we begin to develop a more versatile and complex multi-cell model. The simple model is validated using experimental load-displacement results from laboratory tests: The recorded displacements are used as input values and the measured force data are simulated with the model. The optimal model parameters are estimated using the Levenberg-Marquardt method and a very good agreement between the experimental results and the model calculations is shown. However, not all parts of the model are active in the loading phase of the experiment, so we extended the validation of the model to the simulation of the relaxation behaviour. In this stage, the other model parameters are activated and the simulation results are consistent with the literature. At this stage, we have estimated the parameters only for the two-cell uniaxial model, but further work will include results for the multi-cell model.