• Smart Structures and Systems
• /
• 제32권4호
• /
• pp.235-251
• /
• 2023

A method that can estimate global deformation and internal forces using a limited amount of displacement data and based on the shape superposition technique and a neural network has been recently developed. However, it is difficult to directly measure sufficient displacement data owing to the limitations of conventional displacement meters and the high cost of global navigation satellite systems (GNSS). Therefore, in this study, the previously developed estimation method was extended by combining displacement, slope, and strain to improve the estimation accuracy while reducing the need for high-cost GNSS. To validate the proposed model, the global deformation and internal forces of a cable-stayed bridge were estimated using limited multi-response data. The effect of multi-response data was analyzed, and the estimation performance of the extended method was verified by comparing its results with those of previous methods using a numerical model. The comparison results reveal that the extended method has better performance when estimating global responses than previous methods.

• International Journal of Contents
• /
• 제15권1호
• /
• pp.58-63
• /
• 2019

The objective of this study was to explore a specific method and strategy for 'Global Leadership Program Model' in order to enhance global leadership, which will emphasize the aspect of open mind and attitude toward diversity, cross-culture, communication, and global manner. This research explored the concept and characteristics of global leadership and competency based education, and analyzed effectiveness of satisfaction and participation on global leadership programs implemented in K University and analyzed the learners' recognition on the experience. Also, the research integrated the values of global leadership with the strategies of competency-based education, and finally developed 'Global Leadership Program Model'. As a result, 'Global Leadership Program Model' might be able to help students use knowledge and skill in various contexts, and serve in the community with responsibility. It is expected that students could be facilitated to perform task and role communicating with others, and they might know exactly what learning outcome they are required to establish and what standard is used to evaluate the performance, so that this environment might motivate them and encourage them to follow the learning process more effectively.

• Kyungpook Mathematical Journal
• /
• 제47권2호
• /
• pp.239-251
• /
• 2007

We show how the minimization can be used to solve the quadratic matrix equation and then compare two different types of conjugate gradient method which are Polak and Ribi$\acute{e}$re version and Fletcher and Reeves version. Finally, some results of the global and local convergence are shown.

• Journal of applied mathematics & informatics
• /
• 제22권1_2호
• /
• pp.461-466
• /
• 2006

In this paper, an algorithm with a new Armijo-type line search is proposed that ensure global convergence of a correlative Polak-Ribiere conjugate method for the unconstrained minimization of non-convex differentiable function.

• 대한수학회보
• /
• 제50권1호
• /
• pp.73-81
• /
• 2013

In this paper, an efficient hybrid nonlinear conjugate gradient method is proposed to solve general unconstrained optimization problems on the basis of CD method [2] and DY method [5], which possess the following property: the sufficient descent property holds without any line search. Under the Wolfe line search conditions, we proved the global convergence of the hybrid method for general nonconvex functions. The numerical results show that the hybrid method is especially efficient for the given test problems, and it can be widely used in scientific and engineering computation.

• Journal of applied mathematics & informatics
• /
• 제31권3_4호
• /
• pp.353-363
• /
• 2013

A variant of the global conjugate gradient method for solving general linear systems with multiple right-hand sides is proposed. This method is called as the global conjugate gradient linear least squares (Gl-CGLS) method since it is based on the conjugate gradient least squares method(CGLS). We present how this method can be implemented for the image deblurring problems with Neumann boundary conditions. Numerical experiments are tested on some blurred images for the purpose of comparing the computational efficiencies of Gl-CGLS with CGLS and Gl-LSQR. The results show that Gl-CGLS method is numerically more efficient than others for the ill-posed problems.

• Management Science and Financial Engineering
• /
• 제13권1호
• /
• pp.1-24
• /
• 2007

I propose new combined randomized methods for global optimization problems. These methods are based on the Nested Partitions(NP) method, a useful method for simulation optimization which guarantees global optimal solution but has several shortcomings. To overcome these shortcomings I hired various statistical selection methods and combined with NP method. I first explain the NP method and statistical selection method. And after that I present a detail description of proposed new combined methods and show the results of an application. As well as, I show how these combined methods can be considered in case of computing budget limit problem.

• 생물정신의학
• /
• 제7권2호
• /
• pp.180-185
• /
• 2000

Objective : The present study was designed to compare Global Field Power Measurement and conventional method in P300 determination. Method : The subjects were composed of patients(N=20) with schizophrenia by DSM-IV and normal controls(N=20). The auditory event related potential P300 was measured by "oddball paradigm". P300 components were determined by Global Field Power Measurement and conventional method at 5 electrodes(Fz, Cz, Pz, $T_3$, $T_4$). Results : P300 amplitudes of patients were smaller than those of controls across all electrodes and in both methods, but there was no differential power in P300 determination between two methods. Asymmetry of auditory event-related potential P300 was not shown between patients with schizophrenia and normal controls. Conclusion : It is implicated that it depends on clinical situations and research purposes what method of P300 determination will be more appropriate for patients with schizophernia.

• 대한기계학회논문집A
• /
• 제24권6호
• /
• pp.1529-1539
• /
• 2000

A newly developed optimization method which uses the genetic algorithm combined with the sensitivity analysis is presented in this paper. The genetic algorithm is a probabilistic method, searching the optimum at several points simultaneously, requiring only the values of the object and constraint functions. It has therefore more chances to find global solution and can be applied various problems. Nevertheless, it has such shortcomings that even it approaches the optimum rapidly in the early stage, it slows down afterward and it can't consider the constraints explicitly. It is only because it can't search the local area near the current points. The traditional method, on the other hand, using sensitivity analysis is of great advantage in searching the near optimum. Thus the combination of the two techniques makes use of the individual advantages, that is, the superiority both in global searching by the genetic algorithm and in local searching by the sensitivity analysis. Application of the method to the several test functions verifies that the method suggested is very efficient and powerful to find the global solutions, and that the constraints can be considered properly.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2004년도 추계학술대회
• /
• pp.817-822
• /
• 2004

This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.