• Proceedings of the KSR Conference
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• 2003.05a
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• pp.376-381
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• 2003

This study is focused on the dynamic response of curved bridge when the rubber tired AGT vehicles is running with alternative articulations. For the analytic approach, there is necessary for the three dimensional vehicle model with 11 degree of freedom and the three dimensional curved bridge model by means of finite element method. It can be described by conventional Lagrangian formula with respect to the dynamic interactions between vehicles and its met bridge. The formula is implemented by Fortran language on the simulation program designated BADIA II(Bridge-AGT Dynamic Interaction Analysis II). The solutions of the formula are derived by Newmark- ${\beta}$ method. The BADIA II is for the dynamic interactions between vehicle and curved bridge in terms of the roughness of running surface and guide rail. The applicability of the BADIA II is verified in terms of displacement and modal frequency. This study is described that the dynamic interactive behaviors between the rubber tired AGT vehicle and curved bridge in terms of the radius of curvatures of curved bridge, vehicle articulations, vehicle speeds, vehicle weights, flatness of running surface and roughness of guide rail using BADIA II.

• Survey Research
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• v.12 no.2
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• pp.89-112
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• 2011

This study shows the results of constructing panel data using Farm Household survey and presents some examples of empirical application. This study shows that ex post constructed panel data using repeated cross-sectional survey can be used in various dynamic analyses. This paper also shows that the well known difficult problem of longitudinal weights can be easily solved by using the existing cross-sectional weights in original cross-section data. Based on these results, we propose that the National Statistical Office not only try to construct panel data, but also construct panel data by using existing repeated cross-section data. The benefits of this approach seems to be very big in establishment survey.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.349-351
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• 2004

The classical dynamic backpropagation learning algorithm has the problems of learning speed and the determine of learning parameter. The Extend Kalman Filter(EKF) is used effectively for a state estimation method for a non linear dynamic system. This paper presents a learning algorithm using Dual Extended Kalman Filter(DEKF) for Fully Recurrent Neural Network(FRNN). This DEKF learning algorithm gives the minimum variance estimate of the weights and the hidden outputs. The proposed DEKF learning algorithm is applied to the system identification of a nonlinear SISO system and compared with dynamic backpropagation learning algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.142-147
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• 1999

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.254-262
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• 2008

In this paper, we propose an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for full dynamics of nonlinear flight systems. It is assumed that the model uncertainties such as structured and unstrutured uncertainties, and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate the model uncertainties of nonlinear flight systems, and an adaptive DSC technique is extended for the disturbance attenuation of nonlinear flight systems. All weights of SRWNNs are trained on-line by the smooth projection algorithm. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance nom external disturbances can be obtained. Finally, we present the simulation results for a nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

• Journal of KSNVE
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• v.10 no.1
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• pp.97-106
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• 2000

The dynamic behavior of crankshaft-bearing system in scroll compressor has been investigated using the combined methodologies of finite elements and transfer matrices. The finite element formulation is proposed including the field element for a shaft section and the point element at balancer weight locations, bearing locations, etc., whereas the conventional method is used with the elements. The Houbolt method is used to consider the time march for the integration of the system equations. The linear stiffness and damping coefficients are calculated for a finite cylindrical fluid-film bearing by solving the Reynolds equation, using finite difference method. The orbital response of crankshaft supported on the linear bearing model is obtained, considering balancer weights of motor rotor. And, the steady state displacement of crankshaft are compared with a variation in balancer weight. The loci of crankshaft at bearing locations are composed of the synchronous whirl component and the non-synchronous whirl component.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1386-1394
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• 2016

Pyramid fusion usually adjusts the Laplacian weights of pixels of the input images by evaluating predefined criteria. This has advantages that it can selectively express intense color and enhance the contrast when applied to HDR exposure fusion. But it may cause noise because the weights are determined by pixel importance without considering the interdependent pixel relationship that constitutes a scene. This paper proposes a fusion method using simple weight criteria generated from the gray pixel values, which is expected to preserve the interdependent relationship and improve execution speed. In order to evaluate the performance of the proposed method we examine a homogeneity measure, H and compare the execution time for both methods. The proposed method is found to be more advantageous with respect to homogeneity and execution speed.

• Structural Engineering and Mechanics
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• v.58 no.1
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• pp.121-142
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• 2016

The national standard being used in Turkey for suspended ceiling systems (SCS) regulates material and dimensional properties but does not contain regulations regarding installation instructions which cause substandard applications of SCSs in practice. The lack of installation instructions would potentially affect the dynamic performance of these systems. Also, the vast majority of these systems are manufactured using substandard low-quality materials, and this will inevitably increase SCS related damages during earthquakes. The experimental work presented here focuses on the issue of dynamic performance of SCSs with different types of carrier systems (lay-on and clip-in systems), different weight conditions, and material-workmanship qualities. Moreover, the effects of auxiliary fastening elements, so called seismic perimeter clips, in improving the dynamic performance of SCSs were experimentally investigated. Results show that clip-in ceiling system performs better than lay-on system regardless of material and workmanship qualities. On the other hand, the quality aspect becomes the most important parameter in affecting the dynamic performance of lay-on type systems as opposed to tile weights and usage of perimeter clips. When high quality system is used, tile weight does not change the performance of lay-on system, however in poor quality system, tile weight becomes an important factor where heavier tiles considerably decrease the performance level. Perimeter clips marginally increase the dynamic performance of lay-on ceiling system, but it has no effect on the clip-in ceiling system under the shaking levels considered.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.740-743
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• 1998

This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.