• Journal of applied mathematics & informatics
• /
• v.7 no.1
• /
• pp.41-60
• /
• 2000

In this paper we consider a series of algorithms for calculating radicals of matrix polynomial equations. A particular aspect of this problem arise in author's work. concerning parameter identification of linear dynamic stochastic system. Special attention is given of searching the solution of an equation in a neighbourhood of some initial approximation. The offered approaches and algorithms allow us to receive fast and quite exact solution. We give some recommendations for application of given algorithms.

• Journal of applied mathematics & informatics
• /
• v.5 no.1
• /
• pp.141-152
• /
• 1998

Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.

• Journal of applied mathematics & informatics
• /
• v.24 no.1_2
• /
• pp.155-165
• /
• 2007

We consider a possible generalization of nondeterministic finite automata. The goals of this consideration are: to apply some obtained algorithms for various problems of minimization of classical nondeterministic automata; to use such automata for describing practical anytime algorithms for the same problems of minimization; to simplify some proofs for algorithms of simplification for usual nondeterministic automata.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.17 no.4
• /
• pp.343-350
• /
• 2004

This study is on control gain estimation of energy dissipation control algorithms. Velocity feedback saturated, bang bang, and energy gain control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback saturated and energy-gain control algorithms, and chattering problem in bang bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.12 no.3
• /
• pp.385-396
• /
• 1999

In the process of structural design for large-scale structures with several thousands of degrees of freedom, a plethora of structural calculations with large amount of data storage are required to obtain the forces and displacements of the members. However, current computational environment with single microprocessor such as a personal computer or a workstation is not capable of generating a high-level of efficiency in structural analysis and design process for large-scale structures. In this paper, a high-performance parallel computing system interconnected by a network of personal computers is proposed for an efficient structural analysis. Two distributed structural analysis algorithms are developed in the form of distributed or parallel preconditioned conjugate gradient (DPCG) method. To enhance the performance of the developed distributed structural analysis algorithms, the number of communications and the size of data to be communicated are minimized. These algorithms are applied to the structural analyses of three large space structures as well as a 144-story tube-in-tube framed structure.

• Journal of The Korean Association of Information Education
• /
• v.23 no.6
• /
• pp.639-653
• /
• 2019

The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2004.10a
• /
• pp.143-149
• /
• 2004

In this paper, an automation model for drift design of high-rise buildings using resizing algorithms is proposed. Drift, in the model, includes the maximum lateral displacement at the top and inter-story drifts of a high-rise building subjected to both wind and seismic load. Resizing algorithms for high-rise buildings in various systems and material developed in previous researches are used as a drift control module. As an input to drift control algorithms, member forces for calculation of member displacement participation factors are obtained from commonly-used commercial softwares. The automation model is composed of 4 modules: initial modeling, drift control, stress check, and final verification modules. Each module in the model is described in detail in this paper.

• Advances in Computational Design
• /
• v.5 no.3
• /
• pp.209-231
• /
• 2020

In order to evaluate the performance of three heuristic optimization algorithms, namely, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO) for optimal stacking sequence of laminated composite plates with respect to critical buckling load and non-dimensional natural frequencies, a multi-objective optimization procedure is developed using the weighted summation method. Classical lamination theory and first order shear deformation theory are employed for critical buckling load and natural frequency computations respectively. The analytical critical buckling load and finite element calculation schemes for natural frequencies are validated through the results obtained from literature. The comparative study takes into consideration solution and computational time parameters of the three algorithms in the statistical evaluation scheme. The results indicate that particle swarm optimization (PSO) considerably outperforms the remaining two methods for the special problem considered in the study.

• Korean Journal of Computational Design and Engineering
• /
• v.8 no.4
• /
• pp.212-221
• /
• 2003

In order to reduce the lead-time and cost, the technology of rapid prototyping (RP) has been widely used. A new rapid prototyping process, transfer-type variable lamination manufacturing process by using expandable polystyrene foam (VLM-ST), has been developed to reduce building time, apparatus cost and additional post-processing. At the same time, VLM Slicer, the CAD/CAM software for VLM-ST has been developed. In this study, algorithms for accuracy improvement of VLM-ST, which include offset and overrun of a cutting path and generation of a reference shape are developed. Offset algorithm improves cutting accuracy, overrun algorithm enables the VLM-ST process to make a shape of sharp edge and reference shape generation algorithm adds additional shape which makes off-line lamination easier. In addition, proposed algorithms are applied to practical CAD models for verification.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.3
• /
• pp.305-312
• /
• 2014

This research deals with a problem that minimizes makespan in a non-identical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is large, we propose four heuristic algorithms including genetic algorithm based heuristics to solve the practical big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.