• Proceedings of the KSME Conference
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• 2001.11a
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• pp.533-538
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• 2001

This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a genetic algorithm and a local concentrate search algorithm (e. g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.241-241
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• 2000

In this Paper, we present a new efficient algorithm that can segment an object in the image. There are many algorithms for segmentation and many studies for criteria or threshold value. But, if the environment or brightness is changed, their would not be suitable. Accordingly, we apply a clustering algorithm for adopting and compensating environmental factors. And applying labeling method, we try arranging segment by the similarity that calculated with the fuzzy algorithm. we also present simulations for searching an object and show that the algorithm is somewhat more efficient than the other algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.3
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• pp.173-181
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• 2012

The size and layout of user interface components need to be optimally designed in terms of reachability, visibility, clearance, and compatibility in order for efficient and effective use of products. The present study develops an ergonomic design method which optimizes the size and layout of user interface components using adaptive genetic algorithm. The developed design method determines a near-optimal design which maximizes the aggregated score of 4 ergonomic design criteria (reachability, visibility, clearance, and compatibility). The adaptive genetic algorithm used in the present study finds a near-optimum by automatically adjusting the key parameter (probability of mutation) of traditional genetic algorithm according to the characteristic of current solutions. Since the adaptive mechanism partially helps to overcome the local optimality problem, the probability of finding the near-optimum has been substantially improved. To evaluate the effectiveness of the developed design method, the present study applied it to the user interface design for a portable wireless communication radio.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.434-438
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• 2008

Massive data are continuously produced with a data rate of over several terabytes every day. These applications need effective clustering algorithms to achieve an overall high performance computation. In this paper, we propose ancestor as cluster center based approach to clustering, the K-means algorithm using ancestor. We modify the K-means algorithm. We present a clustering architecture and a clustering algorithm that minimize of I/Os and show a performance with excellent. In our experimental performance evaluation, we present that our algorithm can improve the I/O speed and the query processing time.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.2 s.152
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• pp.139-147
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• 2007

The ultimate goal of structural design is to find the optimal design results which satisfies both safety and economy at the same time. Optimum design has been studied for the last several decades and is being studied. in this study, an optimum algorithm which is based on the genetic algorithm has been applied to the multi-object problem to obtain the optimum solutions which minimizes structural weight and construction cost of panel blocks in ship structures at the same time. Mathematical problems are dealt at first to justify the reliability of the present optimum algorithm. And then the present method has been applied to the panel block model which can be found in ship structures. From the present findings it has been seen that the present optimum algorithm can reasonably give the optimum design results.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.97-139
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• 2002

The aim of the present study is to find a good quality user equilibrium assignments under time varying condition. For this purpose, this study introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it develops a novel solution algorithm that does not need evaluation of the objective function by modifying the Schittenhelm (1990)'s algorithm. This novel algorithm turns out to be efficient and convenient compared to the conventional Frank-Wolfe (1956) algorithm because the former finds solutions based on routes rather than links so that it can maintain correct flow propagation intrinsically in the time-varying network conditions. The application of dynamic user equilibrium (DUE) assignment model with this novel solution algorithm to test networks including medium-sized one shows that the present DUE assignment model gives rise to high quality discrete time solutions when we adopt the deterministic queuing model for a link performance function, and we associate flows and costs in a proper way.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.319-325
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• 2001

Recently. AGV systems are used to serve the raw material to each work stations automatically. There exists a trade-off between the adequate service supply and the number of purchased AGVs. Also, to reduce the overall production cost, the amount of inventory hold on the shop floor should be considered. In this paper, we present a heuristic technique for determining the number of AGVs which includes the net present fixed costs of each station, each purchased AGV, delivering cost, stock inventory cost, and safety stock inventory cost. Secondly, by using a genetic algorithm, the optimal number of AGVs and the optimal reorder quantity at each station are decided. Lastly, to verify then heuristic algorithm, we have done a computer simulation with different GA parameters.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.63-68
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• 2003

The Grid[1] is a communication service that collaborates dispersed high performance computers so that those can be shared and worked together. So, the Grid enables a researcher to analyze a huge-sized problem which was impossible by using local resources. However, diverse communication speeds among computing resources and heterogeneity of computing resources can reduce parallel efficiency in the Grid, The present paper focuses on the development of an efficient load balancing algorithm suitable for the Grid. Proposed algorithm classifies the whole processors into several groups with relatively faster communication speeds. Computational domain is firstly partitioned to each group and then to the processor level considering the performance of each processor. Developed algorithm is validated in the homogeneous system by comparing the present result with the result of equally partitioned meshes and then applied to the heterogeneous system. Additionally, the present algorithm is expanded to be able to solve the decomposed domains and applied to some problems.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.184-191
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• 1999

The k most vital arcs (k-MVA) of a maximum flow problem is defined as those k arcs whose simultaneous removal from the network causes the greatest decrease in the throughput capability of the remaining system between a specified pair of nodes. In this study, we present a method for determining all the k-MVA in maximum flow problem using a minimal cardinality cut algorithm and k-th minimal cut ranking algorithm. For ranking cardinality cuts, we use Hamacher's ranking algorithm for cut capacity and by comparing present residual capacity of cardinality cut with expected residual capacity of next cardinality cut, we also present termination condition for this algorithm. While the previous methods cannot find all the alternatives for this problem, a method presented here has advantage of determining all the k-MVA.