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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.1
- 수록면
- 58 - 65 (8page)
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초록· 키워드
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Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.
목차
등록된 정보가 없습니다.
참고문헌 (10)
참고문헌 신청
Bianchi, L. / 2009 / A Survey on Metaheuristics for Stochastic Combinatorial Optimization / Natural Computing 8:239~287
Dorigo, M. / 1996 / The Ant System : Optimization by a Colony of Cooperating Agents, Systems, Man, and Cybernetics, Part B: Cybernetics / IEEE Transactions on 26(1):29~41
Gao, X.Z / 2009 / Studies in Computational Intelligence :39~51
Geem, Z. W. / 2001 / A New Heuristic Optimization Algorithm : Harmony Search / Simulation 76:60~68
Kattanl, A / 2010 / Harmony Search Based Supervised Training of Artificial Neural Networks / International Conference of Intelligent Systems, Modelling And Simulation :105~110
Dorigo, M. / 1996 / The Ant System : Optimization by a Colony of Cooperating Agents, Systems, Man, and Cybernetics, Part B: Cybernetics / IEEE Transactions on 26(1):29~41
Gao, X.Z / 2009 / Studies in Computational Intelligence :39~51
Geem, Z. W. / 2001 / A New Heuristic Optimization Algorithm : Harmony Search / Simulation 76:60~68
Kattanl, A / 2010 / Harmony Search Based Supervised Training of Artificial Neural Networks / International Conference of Intelligent Systems, Modelling And Simulation :105~110
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