• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.10
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• pp.1621-1626
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• 2001

The structural optimization have been carried out in the continuous design space or in the discrete design space. Methods fur discrete variables such as genetic algorithms , are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete des inn space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions leer constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• Korean Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.107-121
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• 1996

An optimization procedure is proposed to determine the optimal stacking sequence on the buckling of laminated composite plates with midplane symmetry under various loading conditions. Classical lamination theory is used for the determination of the critical buckling load of simply supported angle-ply laminates. Analysis is performed by the Galerkin method and Rayleigh-Ritz method. The approximate solution of buckling is replaced by the algorithms that produce generalized eigenvalue problem. Direct search technique is employed to solve the optimization problem effectively. A series of computations is carried out for plates having different aspect ratios, different load ratios and different number of lay-ups.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.249-250
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• 2008

본 논문에서는 Interval Type-2 TSK 퍼지 논리 시스템을 설계하고 기존의 Type-1 TSK 퍼지 논리 시스템과 비교 분석한다. Type-1 TSK 퍼지 논리 시스템과 Interval Type-2 TSK 퍼지 논리 시스템을 비교하기 위해 노이즈에 영향을 받은 목적 데이터를 사용한다. 유전자 알고리즘을 사용하여 전반부의 중심값의 학습률과 후반부 계수값의 학습률을 결정한다.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.583-591
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• 2000

Caching mechanisms have been studied extensively to buffer the speed gap of hierarchical storages in the context of cache memory, paging system, and buffer management system. As the wide-area distributed environments such as the WWW extend broadly, caching of remote objects becomes more and more important. In the wide-area distributed environments, the cost and the benefit of caching an object is not uniform due to the location of the object; which should be considered in the cache replacement algorithms. For online operation, the time complexity of the replacement algorithm should not be excessive. To date, most replacement algorithms for the wide-area distributed environments do not meet both the non-uniformity of objects and the time complexity constraint. This paper proposes a replacement algorithm which considers the non-uniformity of objects properly; it also allows for an efficient implementation. Trace-driven simulations show that proposed algorithm outperforms existing replacement algorithms.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.432-435
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• 1989

This paper presents an algorithm for electric field analysis which is essential to insulation design of extra-high voltage oil-filled cable accessories using finite element method. Governing equation is induced by electromagnetic equation. Variational method is adopted for FEN formulation. Automatic mesh generation which saves time and labor is introduced for the input data. The application results of proposed algorithms were used for insulation design to develop 345kV cable joint.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.27-34
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• 2005

Iterative detection (ID) has proven to be a near-optimal solution for concatenated Finite State Machines (FSMs) with interleavers over an additive white Gaussian noise (AWGN) channel. When perfect channel state information (CSI) is not available at the receiver, an adaptive ID (AID) scheme is required to deal with the unknown, and possibly time-varying parameters. The basic building block for ID or AID is the soft-input soft-output (SISO) or adaptive SISO (A-SISO) module. In this paper, Reduced State SISO (RS-SISO) algorithms have been applied for complexity reduction of the A-SISO module. We show that serially concatenated CPM (SCCPM) with AID has turbo-like performance over fading ISI channels and also RS-A-SISO systems have large iteration gains. Various design options for RS-A-SISO algorithms are evaluated. Recently developed density evolution technique is used to analyze RS-A-SISO algorithms. We show that density evolution technique that is usually used for AWGN systems is also a good analysis tool for RS-A-SISO systems over frequency-selective fading channels.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.409-414
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• 2021

The growing concerns on the emission of particulate matter has prompted a demand for highly reliable particulate matter forecasting. Currently, several studies on particulate matter prediction use various deep learning algorithms. In this study, we compared the predictive performances of typical neural networks used for particulate matter prediction. We used deep neural network(DNN), recurrent neural network, and long short-term memory algorithms to design an optimal predictive model on the basis of a hyperparameter search. The results of a comparative analysis of the predictive performances of the models indicate that the variation trend of the actual and predicted values generally showed a good performance. In the analysis based on the root mean square error and accuracy, the DNN-based prediction model showed a higher reliability for prediction errors compared with the other prediction models.

• Journal of Korean Society of Steel Construction
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• v.18 no.3
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• pp.361-371
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• 2006

In recent years, to overcome drawbacks related to the aplicati on of classical structural optimization algorithms, various drift design methods based on factores of member displacement participation factors have been developed to size members if they satisfy stiffness criteria. In particular, a resizing algorithm based on dynamic displacement participation factors from the response spectrum analysis has been applied in the drift design of steel structures subjec ted to seismic lateral forces. In this aproach, active members are selected for displacement control based on the displacement participation fa ve members may be taken out and added to the active members for the drift control. The resizing algorithm can be practically and effectively applied to drift design of high-rise buildings however, the inelastic behavior o f the resizing algorithm has not ben evaluated yet. To develop the resizing algorithm considering the performance of nonlinearity as well a s elastic stifness, the evaluation model of resizing algorithm s is developed and aplied to the examples of moment-resisting steel frame, which is one of the simplest structural systems. The inelastic behavior of moment-resisting steel frame designed by the resizing algorithm is also discussed.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

• Structural Engineering and Mechanics
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• v.77 no.3
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• pp.417-439
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• 2021

The geometric nonlinearity has been successfully integrated with the design of steel structural system. Thus, the tubular lattice girder, one application of steel structural systems have already been optimized to obtain an economic design following the completion of computationally expensive design procedure. In order to decrease its computing cost, this study proposes to employ five multi-objective metaheuristics for the design optimization of geometrically nonlinear tubular lattice girder. Then, the employed multi-objective optimization algorithms (MOAs), NSGAII, PESAII, SPEAII, AbYSS and MoCell are evaluated considering their computing performances. For an unbiased evaluation of their computing performance, a tubular lattice girder with varying size-shape-topology and a benchmark truss design with 17 members are not only optimized considering the geometrically nonlinear behavior, but three benchmark mathematical functions along with the four benchmark linear design problems are also included for the comparison purpose. The proposed experimental study is carried out by use of an intelligent optimization tool named JMetal v5.10. According to the quantitative results of employed quality indicators with respect to a statistical analysis test, MoCell is resulted with an achievement of showing better computing performance compared to other four MOAs. Consequently, MoCell is suggested as an optimization tool for the design of geometrically nonlinear tubular lattice girder than the other employed MOAs.