• Title/Summary/Keyword: genetic evaluation

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A Study on Design of Robust $H_\infty$-QFT PSS Using Genetic Algorithm (유전 알고리즘을 이용한 강인한 $H_\infty$-QFT PSS 설계에 관한 연구)

  • 정형환;이정필;박희철;왕용필
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.7
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    • pp.371-380
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    • 2003
  • In this paper, a new design method of H$H_\infty$-Qn PSS using genetic algorithm(GA) is proposed to efficiently damp low frequency oscillations despite the uncertainties and various disturbances of power systems. The selection method of evaluation function is proposed for selecting the robust PSS parameters. All QFT boundaries are satisfied automatically and H$H_\infty$-norm is minimized simultaneously without trial and error procedure. The eigenvalues and the damping ratio of dominant oscillation mode are investigated to evaluate performance of designed controller for one machine infinite bus system. A disturbance attenuation performance is investigated through singular value bode diagram of the system. Dynamic characteristics are considered to verify robustness of the proposed PSS by means of nonlinear simulations under various disturbances for various operating conditions. The results show that the proposed PSS is more robust than conventional PSS.

A Study on the Urinary Metabolite by PAHs and Genetic Susceptibility Markers

  • Chung, Young-Hee;Kim, Dae-Seon;Kang, Tack-Shin
    • Proceedings of the Korean Environmental Health Society Conference
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    • 2005.12a
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    • pp.115-117
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    • 2005
  • In this study, the methods were developed to measure polycyclic aromatic hydrocarbons(PAHs) in the air, metabolites of pyrene and benzo(a)pyrene via human urine, genetic polymorphisms in human buccal cell for evaluation of the health effects about environmental pollution. We have also performed a preliminary molecular epidemiology study on residents in the metropolitan area and workers in workplace for these method applications.

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Evaluation of Genetic Diversity among Korean Wild Codonopsis lanceolata by Using RAPD

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    • Korean Journal of Plant Resources
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    • v.10 no.3
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    • pp.258-264
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    • 1997
  • The introduction of molecular biology methodologies to plant improvement programs offers an invaluable opportunity for extensive germplasm characterization. We have applied the developed technique of random amplification of polymorphic DNA(RAPD)to the analysis of evaluating genetic diversity among Korean wild Codonopsis lanceolata. A total of 340 polymorpic hands were gernerated on agarose- and polyacrylamide-gel by 19 primers of abitrary sequence. grouped by cluster analysis using sample matching coefficients of similarity. Among of the samples. the minimum genetic distance value was obtained between sample no. 1(Girisan) and no. 2(Girisan), and the largest value between sample no. 11(Sulaksan) and no. 17(Sulaksan).In separate cluster dendrograms based on agareose - and polyacryamide-gel. some differences were observed; In the case of agarose gel,41 samples could be devided into 7 groups at below about 0.44 level of distance. However they were divided into 6 gourps at below about 0.40 level of distance in the case of polyacrylamide gel. These results showed that polymophic data in agrose were not grouped to wild plant selected from each mountainous district except for wild plants selected from Sulaksan and Chiaksan. We believe that polyacrylamide-RAPD is a superior method for detecting DNA polymorphism compared to agarose-RAPD method.

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Assessment of the optimal basic reliability in distribution system using genetic algorithm (배전계통 최적기본신뢰도 지수 평가를 위한 유전자 알고리즘의 적용)

  • Kim, Jae-Chul;Han, Seong-Ho;Lee, Bo-Ho;Rhee, Wook;Jang, Jeong-Tae
    • Proceedings of the KIEE Conference
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    • 1995.11a
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    • pp.64-66
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    • 1995
  • This paper presents a new approach to evaluate optimal basic reliability indices of electric distribution systems using genetic algorithm. The use of optimal reliability evaluation is an important aspect of distribution system planning and operation to determine adequacy reliability level of each area. In this paper, the reliability model is based on the analytical method, connecting component failure to load point outage in each section. The proposed method applies genetic algorithm to calculate the optimal values of basic reliability indices, ie. failure rate and repair time, for a load point in the power distribution system, subject to minimizing interruption cost. Test results for the model system are reported in the paper compared with a direct optimization method(gradient projection).

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Evaluation of Genetic Diversity among the Genus Viola by RAPD Markers

  • Oh, Boung-Jun;Ko, Moon-Kyung;Lee, Cheol-Hee
    • Korean Journal of Plant Resources
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    • v.19 no.6
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    • pp.716-720
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    • 2006
  • The genetic diversity among the genus Viola was evaluated using the random amplified polymorphic DNA (RAPD) method. A total of 142 distinct amplification fragments by 18 random primers were scored to perform the cluster analysis with UPGMA. Viola species from the subsection Patellares were clustered into group I to IV. The groups from I to IV were consistent with its morphological taxonomy, series Pinnatae, Chinensis, Variegatae, and Patellares in the subsection Patellares, respectively. Even though V. albida and V. albida var. takahasii were classified in Chinensis, they were assigned into group I. The cluster analysis separated other subsections from Patellares in the section Nomimium. Interestingly, V. verecunda and V. grypoceras in subsections Biobatae and Trigonocarpae, respectively, were clustered into group C with a high similarity coefficient. Therefore, RAPD analysis can be used for providing an alternative classification system to identify genotypes and morphological characters of Viola species.

Parallel Genetic Algorithm for Structural Optimization on a Cluster of Personal Computers (구조최적화를 위한 병렬유전자 알고리즘)

  • 이준호;박효선
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.10a
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    • pp.40-47
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    • 2000
  • One of the drawbacks of GA-based structural optimization is that the fitness evaluation of a population of hundreds of individuals requiring hundreds of structural analyses at each CA generation is computational too expensive. Therefore, a parallel genetic algorithm is developed for structural optimization on a cluster of personal computers in this paper. Based on the parallel genetic algorithm, a population at every generation is partitioned into a number of sub-populations equal to the number of slave computers. Parallelism is exploited at sub-population level by allocationg each sub-population to a slave computer. Thus, fitness of a population at each generation can be concurrently evaluated on a cluster of personal computers. For implementation of the algorithm a virtual distributed computing system in a collection of personal computers connected via a 100 Mb/s Ethernet LAN. The algorithm is applied to the minimum weight design of a steel structure. The results show that the computational time requied for serial GA-based structural optimization process is drastically reduced.

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Application of multi objective genetic algorithm in ship hull optimization

  • Guha, Amitava;Falzaranoa, Jeffrey
    • Ocean Systems Engineering
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    • v.5 no.2
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    • pp.91-107
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    • 2015
  • Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.

A Sequencing Problem with Fuzzy Preference Relation and its Genetic Algorithm-based Solution (퍼지선호관계 순서화 문제와 유전자 알고리즘 기반 해법)

  • Lee, Keon-Myung;Sohn, Bong-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.69-74
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    • 2004
  • A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

A Genetic Algorithm Approach to the Frequency Assignment Problem on VHF Network of SPIDER System

  • Kwon, O-Jeong
    • Journal of the military operations research society of Korea
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    • v.26 no.1
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    • pp.56-69
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    • 2000
  • A frequency assignment problem on time division duplex system is considered. Republic of Korea Army (ROKA) has been establishing an infrastructure of tactical communication (SPIDER) system for next generation and it will be a core network structure of system. VHF system is the backbone network of SPIDER, that performs transmission of data such as voice, text and images. So, it is a significant problem finding the frequency assignment with no interference under very restricted resource environment. With a given arbitrary configuration of communications network, we find a feasible solution that guarantees communication without interference between sites and relay stations. We formulate a frequency assignment problem as an Integer Programming model, which has NP-hard complexity. To find the assignment results within a reasonable time, we take a genetic algorithm approach which represents the solution structure with available frequency order, and develop a genetic operation strategies. Computational result shows that the network configuration of SPIDER can be solved efficiently within a very short time.

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A non-destructive method for elliptical cracks identification in shafts based on wave propagation signals and genetic algorithms

  • Munoz-Abella, Belen;Rubio, Lourdes;Rubio, Patricia
    • Smart Structures and Systems
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    • v.10 no.1
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    • pp.47-65
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    • 2012
  • The presence of crack-like defects in mechanical and structural elements produces failures during their service life that in some cases can be catastrophic. So, the early detection of the fatigue cracks is particularly important because they grow rapidly, with a propagation velocity that increases exponentially, and may lead to long out-of-service periods, heavy damages of machines and severe economic consequences. In this work, a non-destructive method for the detection and identification of elliptical cracks in shafts based on stress wave propagation is proposed. The propagation of a stress wave in a cracked shaft has been numerically analyzed and numerical results have been used to detect and identify the crack through the genetic algorithm optimization method. The results obtained in this work allow the development of an on-line method for damage detection and identification for cracked shaft-like components using an easy and portable dynamic testing device.