• 제목/요약/키워드: Genetic characteristic

검색결과 351건 처리시간 0.034초

유전알고리즘에 의한 강봉의 구조특성행렬 산출법 (Identification of Structural Characteristic Matrices of Steel Bar by Genetic Algorithm)

  • 박석주;제해광;이금주;박영범;박경일
    • 한국소음진동공학회논문집
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    • 제20권10호
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    • pp.946-952
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    • 2010
  • A method for the identification of structural characteristic parameters of a steel bar in the matrices form such as stiffness matrices and mass matrices from frequency response function(FRF) by genetic algorithm is proposed. As the method is based on the finite element method(FEM), the obtained matrices have perfect physical meanings if the FRFs got from the analysis and the FRFs from the experiments were well coincident each other. The identified characteristic matrices from the FRFs with maximun 40 % of random errors by the genetic algorithm are coincident with the characteristic matrices from exact FEM FRFs well each other. The fitted element diameters by using only 2 points experimental FRFs are similar to the actual diameters of the bar. The fitted FRFs are good accordance with the experimental FRFs on the graphs. FRFs of the rest 9 points not used for calculating could be fitted even well.

Variable Structure Control with Fuzzy Reaching Law Method Using Genetic Algorithm

  • Sagong, Seong-Dae;Choi, Bong-Yeol
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1430-1434
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    • 2003
  • In this paper, for the fuzzy-reaching law method which has the characteristic of elimination of chattering at sliding mode as well as the characteristic of fast response at the design of variable structure controller with reaching law, optimal solutions for the determination of parameters of fuzzy membership functions by using genetic algorithm are proposed. Generally, the design of fuzzy controller has difficulties in determining the parameters of fuzzy membership functions by using a tedious trial-and-error process. To overcome these difficulties, this paper develops genetic algorithm of an optimal searching method based on genetic operation, and to verify the validity of this proposed method it is simulated through 2 link robot manipulator.

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Integrated diagnostic approach of pediatric neuromuscular disorders

  • Lee, Ha Neul;Lee, Young-Mock
    • Journal of Genetic Medicine
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    • 제15권2호
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    • pp.55-63
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    • 2018
  • Clinical and genetic heterogeneity in association with overlapping spectrum is characteristic in pediatric neuromuscular disorders, which makes confirmative diagnosis difficult and time consuming. Considering evolution of molecular genetic diagnosis and resultant upcoming genetically modifiable therapeutic options, rapid and cost-effective genetic testing should be applied in conjunction with existing diagnostic methods of clinical examinations, laboratory tests, electrophysiologic studies and pathologic studies. Earlier correct diagnosis would enable better clinical management for these patients in addition to new genetic drug options and genetic counseling.

최소좁은세상 셀룰러 유전알고리즘 (Smallest-Small-World Cellular Genetic Algorithms)

  • 강태원
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권11호
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    • pp.971-983
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    • 2007
  • 셀룰러 유전알고리즘(CGAs)은 모집단이 특정한 위상 구조를 갖는 유전알고리즘의 일종이다. 보통의 경우, CGAs의 모집단 공간은 네트워크 이론 측면에서 상대적으로 긴 평균경로길이와 큰 클러스터링계수를 갖는 정규 격자형 위상 구조이다. 평균경로길이가 길면 멀리 떨어진 개체들 사이의 유전적 상호작용이 느리게 일어난다. 따라서 클러스터링계수를 유지하면서 평균경로길이를 줄인다면 개체의 다양성이 유지되면서도 모집단이 보다 빠르게 수렴할 것이다. 이 논문에서는 최소좁은세상 셀룰러 유전알고리즘(SSWCGAs)을 제안한다. SSWCGAs에서 각 개체는 클러스터링이 잘되었으면서도 노드를 연결하는 평균경로길이가 짧은 모집단에 거주하여, 클러스터링에 의한 세부탐색 능력을 유지하면서도 전역탐색을 잘하게 된다. 네 가지 실변수 함수와 두 가지 GA-hard 문제에 대한 실험을 통하여 SSWCGAs가 SGAs 및 CGAs보다 효과적임을 보였다.

유사성 계수를 이용한 군집화 문제에서 유전자와 국부 최적화 알고리듬의 적용 (Application of Genetic and Local Optimization Algorithms for Object Clustering Problem with Similarity Coefficients)

  • 임동순;오현승
    • 대한산업공학회지
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    • 제29권1호
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    • pp.90-99
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    • 2003
  • Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.

유전 알고리즘과 3차원 공간고조파법을 이용한 Soltless Type PMLSM의 최적설계에 관한 연구 (A Study on the Optimum Design of Soltless Type PMLSM Using Genetic Algorithm and 3-D Space Harmonic Method)

  • 이동엽;김규탁
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권8호
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    • pp.463-468
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    • 2004
  • This paper was applied space harmonic method as a characteristic analysis technique for slotless PMLSM. There is advantages of active response to the change of design parameters as well as reduction of the calculation time. The method can be overcome disadvantages of finite element analysis that needs long times calculation, repetitions of pre and post-process. In this paper, 3D-space harmonic method was applied to consider the precise description of end turn coil shape and the changes of characteristic according to changes of length of z-axis direction. The thrust of optimal design was performed using genetic algorithm to enhance the thrust which is the disadvantage of slotless type PMLSM. For design parameters, width of permanent magnet, width of coil, width of coil inner and lengths of z-axis direction were selected. For objective functions. thrust per weight. thrust per volume. multi-objective function was selected.

유전성 암과 유전상담 (Hereditary cancer and genetic counseling)

  • 정승용
    • Journal of Genetic Medicine
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    • 제4권1호
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    • pp.15-21
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    • 2007
  • Hereditary syndromes cause approximately 5 to 10% of overall cancer cases. Cancer related with genetic syndromes are found elsewhere, including stomach, breast, colorectum, ovary, brain and so on. Because hereditary cancers are due to germline mutations, these patients have unique clinical features distinct from sporadic cancer. Generally these features include (i) early age-of onset of cancer, (ii) frequent association with synchronous or metachronous tumors, (iii) frequent bilateral involvement in paired organs (iv) frequent association with other site tumors or characteristic clinical manifestation specific to each genetic syndrome. Due to these differences, the management strategy for patients with hereditary cancer is quite different from that for sporadic cancer. Additionally, there are important screening and surveillance implications for family members. Genetic counselling is prerequisite to these families for risk assessment by pedigree analysis, and guidance to clinical or genetic testing. The genes responsible for these syndromes has recently identified, as a result, genetic testing has become important determining factor in clinical decisions.

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유전알고리즘의 자기동조 방법에 의한 직류 직권모터 모터 속도제어 (Speed Control of DC Series Wound Motor Using a Genetic A1gorithm with Self-Tuning Method)

  • 배종일;제창우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2763-2765
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    • 2003
  • Generally, we made use of PID control for torque control, speed control and stability, Hence, dynamic characteristic of DC motor has been studied for stable drive and accurate speed control by many engineers. But, in this paper, we applied genetic algorithm to current control for robust control and stability In conclusion, we prove that current control of genetic algorithm can be high efficiency.

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A Taguchi Approach to Parameter Setting in a Genetic Algorithm for General Job Shop Scheduling Problem

  • Sun, Ji Ung
    • Industrial Engineering and Management Systems
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    • 제6권2호
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    • pp.119-124
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    • 2007
  • The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.