• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.101-107
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• 2000

A design of the global optimal sliding mode control is presented to control the second order uncertain time varying system with torque limit. With specified ranges of parametric uncertainties and torque limit, the minimum arrival time to reference inputs can be calculated. The proposed control scheme is applied to the motor system carrying loads. The merit of the proposed control scheme is that the arriving time at the reference input, which is the revolution angle, and the maximum allowable acceleration are expressed in a closed form solution. The superior performance of the proposed control scheme is validated by the computer simulation and experiments comparing with other sliding mode controllers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6276-6281
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• 2014

Genetic Algorithms (GAs) are efficient methods for search and optimization problems. On the other hand, there are some problems associated with the premature convergence to local optima of the multimodal function, which has multi peaks. The problem is related to the lack of genetic diversity of the population to cover the search spaces sufficiently. A sharing and crowding method were introduced. This paper proposed strategies to improve the convergence speed and the convergence to the global optimum for solving the multimodal optimization function. These strategies included the random generated sub-population that were well-distributed and spread widely through search spaces. The results of the simulation verified the effects of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.117-128
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• 2001

In order to achieve optimal retrieval, i.e., to find the best match to a query according to a certain similarity measure, the exhaustive search should be performed literally for all the images in a database. However, the straightforward exhaustive search algorithm is computationally expensive in large image databases. To reduce its heavy computational cost, this paper presents a fast exhaustive multi-resolution search algorithm based on image database clustering. Firstly, the proposed algorithm partitions the whole image data set into a pre-defined number of clusters having similar feature contents. Next, for a given query, it checks the lower bound of distances in each cluster, eliminating disqualified clusters. Then, it only examines the candidates in the remaining clusters. To alleviate unnecessary feature matching operations in the search procedure, the distance inequality property is employed based on a multi-resolution data structure. The proposed algorithm realizes a fast exhaustive multi-resolution search for either the best match or multiple best matches to the query. Using luminance histograms as a feature, we prove that the proposed algorithm guarantees optimal retrieval with high searching speed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.620-628
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• 2016

The homotopy algorithm provides a robust method for determining optimal control, in some cases the global minimum solution, as a continuation parameter is varied gradually to regulate the contributions of the nonlinear terms. In this paper, the Successive Backward Sweep (SBS) method, which is insensitive to initial guess, augmented with a homotopy algorithm is suggested. This approach is effective for highly nonlinear problems such as low-thrust trajectory optimization. Often, these highly nonlinear problems have multiple local minima. In this case, the SBS-homotopy method enables one to steadily seek a global minimum.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.3010-3023
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• 1998

GA has a fast convergence speed in searching the one point around optimal value. But it's convergence time increase in searching the region around optimal value because it has no regional searching mechanism. BP has the tendency to converge the local minimum because it has global searching mechanism. To overcome these problems, a method in which a genetic algorithm and a back propagation are applied in turn is proposed in this paper. By using a genetic algorithm, we compute optimal synaptic strength and offset value. And then, these values are fed to the input of the back propagation. This proposed method is superior to each above method in improving the convergence speed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.5
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• pp.125-132
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• 2008

Structural optimization is widely adopted in the design of structures with the development of computer aided design and computer technique recently. By applying the structural optimization in the last decades, designers have gained the design scheme of structures more feasibly and easily. In this paper, an optimal design of one 30-story high rise steel structure is performed considering material non-linearity. Based on finite element analysis and adaptive simulated annealing algorithm, the optimal weight of structure is derived under constraints of allowable yield stress, shear stress and serviceability.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.137-142
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• 2005

유전자 알고리즘은 전체 탐색 공간을 통해 전역 해를 찾는 최적화 알고리즘으로서 복잡한 상태 공간에서 최적 해를 찾기 위해 전통적인 최적화 기법과는 달리 유향성 임의 탐색을 행한다. 또한, 유전적 탐색과 국부 탐색을 결합시킨 복합 유전자 알고리즘은 최적해로의 수렵 속도를 향상시킬 수 있다. 이 논문에서는 함수 최적화를 위해 학습 속도를 개선한 복합 유전자 알고리즘(C-AGA)을 제안한다. 제안한 최적화 알고리즘의 효율을 기존의 복합 유전자 알고리즘 기법(라마키안 진화 및 볼드윈 효과)과 비교 평가하였다. 다양한 함수 최적화 문제에 대하여 제안한 알고리즘이 기존의 방법보다 더 빨리 전역 최적 해를 찾을 수 있음을 증명하였다.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.798-800
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• 2000

전기기기의 구조 및 형상 최적화에 있어서 다양한 제한 사항과 설계방법들을 이용하기 위하여 전역 최대점과 함께 국소 최대점까지 고려할 수 있는 최적화 기법이 요구되고 있다. 다양한 제한사항들을 모두 목적 함수에 포함시킬 경우에 발생하는 여러 가지 문제점들을 해결하고 설계자의 주관적 평가도 활용할 수 있는 새로운 기법을 필요로 한다. 이처럼 다양한 해의 생성과 보존을 필요로 하는 분야에 니체(niche) 개념이 이용될 수 있다. 본 논문에서는 니체 개념을 포함하는 유전 알고리즘을 이용하여 토크의 선형성을 보장하는 토크 모터의 최적 설계를 수행하였다. 최적 설계 결과를 전역 최대점만을 찾는 최적화 기법과 비교하여 그 타당성을 입증하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.23-29
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• 2012

Existing pedestrian and evacuation models generally seek to find locally optimal solutions for the shortest or the least time paths to exits from individual locations considering pedestrian's characteristics (eg. speed, direction, sex, age, weight and size). These models are not designed to produce globally optimal solutions that reduce the total evacuation time of the entire pedestrians in a building when all of them evacuate at the same time. In this study, we suggest a globally optimal model for indoor pedestrian evacuation to minimize the total evacuation time of occupants in a building considering different distributions of them. We used the genetic algorithm, one of meta-heuristic techniques because minimizing the total evacuation time can not be easily solved by polynomial expressions. We found near-optimal evacuation path and time by expressing varying pedestrians distributions using chromosomes and repeatedly filtering solutions. In order to express and experiment our suggested algorithm, we used CA(cellular automata)-based simulator and applied to different indoor distributions and presented the results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.39-45
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• 2007

In this paper, a research has been conducted to find out the optimal combination of central meridian and scale factor of UTM-K to apply for the whole area of Korean peninsula. For this research, various combinations of central meridian and stale factor are set up and the cumulated level or distortion for each combination has been computed and compared to each other. In the case of using the central meridian and scale factor defined in the present UTM-K, the level of distortion shows about $47.0837{\times}10^{-2}$. On the other hand, the minimum distortion which is about $21.0495{\times}10^{-2}$ can be obtained when the $127^{\circ}26'$ for the central meridian and 0.99991 for scale factor are used for computation. Consequently, we can conclude that later result is the optimum combination of central meridian and scale factor for the Korean peninsula.