• Journal of Ocean Engineering and Technology
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• v.18 no.5
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• pp.29-35
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• 2004

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is proposed for identifying a global solution, using continuous zooming factors for optimization problems. In order to improve the local fine-tuning of the GA, we introduced a new method whereby the search space is zoomed around the design variable with the best fitness per 100 generation, resulting in an improvement of the convergence. Furthermore, the reliability of the optimized solution is determined based on the theory of probability, and the parameter used for the successive zooming method is optimized. With parameter optimization, we can eliminate the time allocated for deciding parameters used in SZGA. To demonstrate the superiority of the proposed theory, we tested for the minimization of a multiple function, as well as simple functions. After testing, we applied the parameter optimization to a truss problem and wicket gate servomotor optimization. Then, the proposed algorithm identifies a more exact optimum value than the standard genetic algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.406-414
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• 2002

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is Proposed for identifying a global solution for continuous optimization problems. In order to improve the local fine-tuning capability of GA, we introduced a new method whereby the search space is zoomed around the design point with the best fitness per 100 generation. Furthermore, the reliability of the optimized solution is determined based on the theory of probability. To demonstrate the superiority of the proposed algorithm, a simple genetic algorithm, micro genetic algorithm, and the proposed algorithm were tested as regards for the minimization of a multiminima function as well as simple functions. The results confirmed that the proposed SZGA significantly improved the ability of the algorithm to identify a precise global minimum. As an example of structural optimization, the SZGA was applied to the optimal location of support points for weight minimization in the radial gate of a dam structure. The proposed algorithm identified a more exact optimum value than the standard genetic algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.144-149
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• 1996

The automation of mesh generation in BEM is bery important in numerical analysys field for the time and efficiency. To be solve this problem Probram and Algorithm, to achive purpose of making input data and automation of mesh generation based on Expert system is developed in this study. And function of this program can be rotating and zooming, To prove efficiency and availability of program in result the stress intensity factor which is criteria of fracture mechanics is caculated and compared with other results.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.65-71
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• 1997

The automation of mesh generation in BEM is very important in numerical analysis field for the time and efficiency. In order to this problem, program and algorithm to achive the purpose of making input data and automation of mesh generation based in Expert System are developed in this study. This program has the function of rotating and zooming. The stress intensity factor which is a criteria of fracture mechanics is calculated and compared with other results to prove efficiency and availability of the program in result.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.529-537
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• 2011

In this paper, we propose a stable scale adaptive tracking method that uses centroids of the target colors. Most scale adaptive tracking methods have utilized histograms to determine target window sizes. However, in certain cases, histograms fail to provide good estimates of target sizes, for example, in the case of occlusion or the appearance of colors in the background that are similar to the target colors. This is due to the fact that histograms are related to the numbers of pixels that correspond to the target colors. Therefore, we propose the use of centroids that correspond to the target colors in the scale adaptation algorithm, since centroids are less sensitive to changes in the number of pixels that correspond to the target colors. Due to the spatial information inherent in centroids, a direct relationship can be established between centroids and the scale of target regions. Generally, after the zooming factors that correspond to all the target colors are calculated, the unreliable zooming factors are filtered out to produce a reliable zooming factor that determines the new scale of the target. Combined with the centroid based tracking algorithm, the proposed scale adaptation method results in a stable scale adaptive tracking algorithm. It tracks objects in a stable way, even when the background colors are similar to the colors of the object.