• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.902-908
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• 2006

We propose a scheme for more efficient navigation in a hierarchical file system. In the proposed scheme, a program running in the background computes the degree of relationship between a current file and others, and builds a list of the most related files. The current relationship metric being used by the program is a linear combination of five parameters: the name, the directory path, the type, the created time, and the last accessed time of a file. A simulated annealing algorithm is used in order to determine the weighting factors of the parameters. A set of experiments were conducted in order to access the effectiveness of the proposed scheme.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.321-332
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• 2001

본 논문에서는 반응변수가 두 가지의 값을 갖는 회귀분석에 적용할 수 있는 사영추적회귀를 고려하였다. 회귀모형에 필요한 설명변수들의 선형결합이 하나이고 연결함수의 형태를 사전에 알지 못한다는 가정하에서 모의담금질 기법을 이용하여 모형에 필요한 선형결합을 찾는 알고리즘을 제시하였다. 이진 반응변수의 경우에는 평활모수의 값에 따라 잔차이탈도함수의 반응표면이 단봉의 형태를 갖지 않는 경우가 있어 비동질적 마코프체인을 이용한 모의담금질 기법을 적용하면 효율적으로 선형결합을 탐색할 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.535-538
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• 2003

We employ Genetic Programming (GP) which is optimized with Simulated Annealing (SA) to recognize characteristic of a plan. Its result is described in Laplace function. The algorithm proceeds with automatic PID designs for the plant.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1941-1945
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• 2011

In this paper, we propose a real-time classifier to distinguish humans from livestock by using the spatial integral. The image-difference method and the Expectation Maximization are used to reduce noises in input image. A histogram analysis based on Simulated Annealing and the fuzzy-Bayesian algorithm are used to classify human and livestock. Finally, the experiment results show the validity of the proposed method.

• Korean Management Science Review
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• v.14 no.1
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• pp.77-85
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• 1997

This paper proposes an approach for individual selection in genetic algorithms to improve problem solving efficiency and effectiveness. To investigate the utility of combining simulated annealing with genetic algorithm, two experiment are conducted that compare both the conventional genetic algorithm and suggested approach. Result indicated that suggested approach significantly reduced the required time to find optimal solution in moderate-sized problems under the conditions studied. It is also found that quality of the solutions generated by suggested approach in large- sized problems is greatly improved.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.04a
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• pp.102-109
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• 1999

Two phase simulated annealing algorithm is presented as a structural optimization technique and applied to minimum weight design of space trusses subjected to stress and displacement constraints under multiple loading conditions. Univariate searching algorithm is adopted for automatic selection of initial values of design variables for SA algorithm. The proper values of cooling factors and reasonable stopping criteria for optimum design of space truss structures are proposed to enhance the performance of optimization process. Optimum weights and design solutions are presented for two well-blown example structures and compared with those reported in the literature.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.569-571
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• 1995

This paper compares the simulated annealing and the Hopfield neural network method for an optimal routing in a multistage interconnection network(MIN). The MIN provides a multiple number of paths for ATM cells to avoid cell conflict. Exhaustive search always finds the optimal path, but with heavy computation. Although greedy method sets up a path quickly, the path found need not be optimal. The simulated annealing can find an sub optimal path in time comparable with the greedy method.

• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.337-354
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• 2004

SA, TS, GA and ACS are four of the main algorithms for solving challenging problems of intelligent systems. In this paper we consider Examination Timetabling Problem that is a common problem for all universities and institutions of higher education. There are many methods to solve this problem, In this paper we use Simulated Annealing, Tabu Search, Genetic Algorithm and Ant Colony System in their basic frameworks for solving this problem and compare results of them with each other.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.177-185
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• 2005

We consider the optimization problem of the geostationary satellite orbital positions. which is very fundamental and important in setting up the new satellite launching plan. We convert the problem into a discrete optimization problem. However, the converted problem is too complex to find an optimal solution. Therefore, we develope the solution procedures using simulated annealing technique. The results of applying our method to some examples are reported.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.37-47
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• 1998

Under the cutoff priority discipline, the prioritized channel allocation problem is formulated, which minimizes the overall blocking probability while ensuring the co-channel interference constraints. To deal with the problem more conveniently, the concept of pattern is used. A simulated annealing approach is applied to the problem, and computational experiments show that a high-quality solution is obtained.