• 제목/요약/키워드: Mutation robustness

검색결과 13건 처리시간 0.022초

신경회로망의 학습 알고리듬을 이용하여 돌연변이를 수행하는 새로운 진화 프로그래밍 알고리듬 (A New Evolutionary Programming Algorithm using the Learning Rule of a Neural Network for Mutation of Individuals)

  • 임종화;최두현;황찬식
    • 전자공학회논문지C
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    • 제36C권3호
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    • pp.58-64
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    • 1999
  • 진화 프로그래밍은 두 가지 요소로 특징지을 수 있다. 하나는 선택 방법이고 나머지는 돌연변이 규칙이다. 본 논문에서는 신경회로망의 역전파 학습 알고리듬을 이용하여 돌연변이 연산을 수행하는 새로운 진화 프로그래밍 알고리듬을 제안한다. 신경회로망의 학습 알고리듬에서 현재 오차는 진화 프로그래밍의 개체가 진화해 나가야 할 방향을 지정해 주고, 관성은 개체의 변이에 지금까지의 진화 경향을 더해 주어서 빠르게 전역 최적해를 찾도록 하였다. 표준 테스트 함수를 이용하여 제안된 알고리듬의 성능과 강건함을 확인하였다.

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차분진화 알고리듬을 이용한 전역최적화 (Global Optimization Using Differential Evolution Algorithm)

  • 정재준;이태희
    • 대한기계학회논문집A
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    • 제27권11호
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    • pp.1809-1814
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    • 2003
  • Differential evolution (DE) algorithm is presented and applied to global optimization in this research. DE suggested initially fur the solution to Chebychev polynomial fitting problem is similar to genetic algorithm(GA) including crossover, mutation and selection process. However, differential evolution algorithm is simpler than GA because it uses a vector concept in populating process. And DE turns out to be converged faster than CA, since it employs the difference information as pseudo-sensitivity In this paper, a trial vector and its control parameters of DE are examined and unconstrained optimization problems of highly nonlinear multimodal functions are demonstrated. To illustrate the efficiency of DE, convergence rates and robustness of global optimization algorithms are compared with those of simple GA.

실시간 적응 학습 제어를 위한 진화연산(I) (Evolutionary Computation for the Real-Time Adaptive Learning Control(I))

  • 장성욱;이진걸
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집B
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    • pp.724-729
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    • 2001
  • This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

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혼합형 유전해법을 이용한 비대칭 외판원문제의 발견적해법 (A Heuristic Algorithm for Asymmetric Traveling Salesman Problem using Hybrid Genetic Algorithm)

  • 김진규;윤덕균
    • 산업경영시스템학회지
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    • 제18권33호
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    • pp.111-118
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    • 1995
  • This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

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실시간 진화 알고리듬을 통한 신경망의 적응 학습제어 (Adaptive Learning Control of Neural Network Using Real-Time Evolutionary Algorithm)

  • 장성욱;이진걸
    • 대한기계학회논문집A
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    • 제26권6호
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    • pp.1092-1098
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    • 2002
  • This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

Special Protection and Control Scheme for Transmission Line Overloading Elimination Based on Hybrid Differential Evolution/Electromagnetism-Like Algorithm

  • Hadi, Mahmood Khalid;Othman, Mohammad Lutfi;Wahab, Noor Izzri Abd
    • Journal of Electrical Engineering and Technology
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    • 제12권5호
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    • pp.1729-1742
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    • 2017
  • In designing System Protection Schemes (SPSs) in power systems, protecting transmission network against extreme undesired conditions becomes a significant challenge in mitigating the transmission line overloading. This paper presents an intelligent Special Protection and Control Scheme (SPCS) using of Differential Evolution with Adaptive Mutation (DEAM) approach to obtain the optimum generation rescheduling to solve the transmission line overloading problem in system contingency conditions. DEAM algorithm employs the attraction-repulsion idea that is applied in the electromagnetism-like algorithm to support the mutation process of the conventional Differential Evolution (DE) algorithm. Different N-1 contingency conditions under base and increase load demand are considered in this paper. Simulation results have been compared with those acquired from Genetic Algorithm (GA) application. Minimum severity index has been considered as the objective function. The final results show that the presented DEAM method offers better performance than GA in terms of faster convergence and less generation fuel cost. IEEE 30-bus test system has been used to prove the effectiveness and robustness of the proposed algorithm.

Lifting 기반 1D DWT 영역 상의 강인한 DNA 워터마킹 (A Robust DNA Watermarking in Lifting Based 1D DWT Domain)

  • 이석환;권기룡;권성근
    • 전자공학회논문지
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    • 제49권10호
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    • pp.91-101
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    • 2012
  • 개인 유전정보 또는 대용량 DNA 저장 정보의 보호와 GMO(Genetically Modified Organism) 저작권 보호를 위하여 DNA 서열 워터마킹 연구가 필요하다. 기존 멀티미디어 데이터 워터마킹에서는 강인성 및 비가시성에 대한 성능이 우수한 DCT, DWT, FMT(Fourer-Mellin transform) 등 주파수 기반으로 설계되어졌다. 그러나 부호 영역 서열의 주파수 기반 워터마킹은 아미노산 보존성을 유지하면서 변환 및 역변환을 수행하여야 하므로, 워터마크 삽입에 대한 상당한 제약을 가진다. 따라서 본 논문에서는 변이 강인성, 아미노산 보존성 및 보안성을 가지는 부호 영역 서열의 Lifting 기반 DWT 변환 계수를 이용한 워터마킹을 제안하며, 주파수 기반 DNA 서열 워터마킹에 대한 가능성을 제기한다. 실험 결과로부터 제안한 방법이 10%의 포인트 변이와 5%의 삽입 및 삭제 변이에 대한 강인성을 가지며, 아미노산 보존성 및 보안성을 가짐을 확인하였다.

Particle Swarm Assisted Genetic Algorithm for the Optimal Design of Flexbeam Sections

  • Dhadwal, Manoj Kumar;Lim, Kyu Baek;Jung, Sung Nam;Kim, Tae Joo
    • International Journal of Aeronautical and Space Sciences
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    • 제14권4호
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    • pp.341-349
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    • 2013
  • This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm, of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are obtained with less function evaluations, and less computation time.

DNA chip technology

  • 이상엽;윤성호;최종길;임근배
    • 한국생물공학회:학술대회논문집
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    • 한국생물공학회 2000년도 추계학술발표대회 및 bio-venture fair
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    • pp.119-122
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    • 2000
  • Biological science is being revolutionized by the availability of much sequence information from many genome project With the advanced technology at hand, main trend in biological research is rapidly changing from a structural DNA analysis to understanding cellular function of the DNA sequences. Combined with mechanics, computer, bioinformatics and other advanced technologies, DNA chip technology provides numerous applications because of its robustness, accuracy, and automation. DNA chip is expected to become an indispensable tool in fields of biology, biotechnology, drug discovery, and other application areas. DNA chip can be used for mutation and polymorphism detection, gene expression monitoring and phenotypic analysis as well. If DNA chip is used for the development of pharmaceutical products, it can considerably reduce the cost and time for the entire process of drug discovery and development, and can also contribute in developing personal drugs.

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부호 영역 DNA 시퀀스 기반 강인한 DNA 워터마킹 (Robust DNA Watermarking based on Coding DNA Sequence)

  • 이석환;권성근;권기룡
    • 전자공학회논문지CI
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    • 제49권2호
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    • pp.123-133
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    • 2012
  • 본 논문에서는 DNA 시퀀스의 불법 복제 및 변이 방지와 개인 정보 침해 방지, 또는 인증을 위한 DNA 워터마킹에 대하여 논의하며, 변이에 강인하고 아미노산 보존성을 가지는 부호영역 DNA 시퀀스 기반 DNA 워터마킹 기법을 제안한다. 제안한 DNA 워터마킹은 부호 영역의 코돈 서열에서 정규 특이점에 해당되는 코돈들을 삽입 대상으로 선택되며, 워터마크된 코돈이 원본 코돈과 동일한 아미노산으로 번역되도록 워터마크가 삽입된다. DNA 염기 서열은 4개의 문자 {A,G,C,T}로 (RNA은 {A,C,G,U}) 구성된 문자열이다. 제안한 방법에서는 워터마킹 신호처리에 적합한 코돈 부호 테이블을 설계하였으며, 이 테이블에 따라 코돈 서열들을 정수열로 변환한 다음 원형 각도 형태의 실수열로 재변환한다. 여기서 코돈은 3개의 염기들로 구성되며, 64개의 코돈들은 20개의 아미노산으로 번역된다. 선택된 코돈들은 아미노산 보존성을 가지는 원형 각도 실수 범위 내에서 인접 코돈과의 원형 거리차 기준으로 워터마크에 따라 변경된다. HEXA와 ANG 시퀀스를 이용한 $in$ $silico$ 실험을 통하여 제안한 방법이 기존 방법에 비하여 아미노산 보존성을 가지면서 침묵 변이와 미스센스 변이에 보다 강인함을 확인하였다.