• 제목/요약/키워드: Genetic evaluation

검색결과 886건 처리시간 0.025초

Comparison of the estimated breeding value and accuracy by imputation reference Beadchip platform and scaling factor of the genomic relationship matrix in Hanwoo cattle

  • Soo Hyun, Lee;Chang Gwon, Dang;Mina, Park;Seung Soo, Lee;Young Chang, Lee;Jae Gu, Lee;Hyuk Kee, Chang;Ho Baek, Yoon;Chung-il, Cho;Sang Hong, Lee;Tae Jeong, Choi
    • 농업과학연구
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    • 제49권3호
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    • pp.431-440
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    • 2022
  • Hanwoo cattle are a unique and historical breed in Korea that have been genetically improved and maintained by the national evaluation and selection system. The aim of this study was to provide information that can help improve the accuracy of the estimated breeding values in Hanwoo cattle by showing the difference between the imputation reference chip platforms of genomic data and the scaling factor of the genetic relationship matrix (GRM). In this study, nine sets of data were compared that consisted of 3 reference platforms each with 3 different scaling factors (-0.5, 0 and 0.5). The evaluation was performed using MTG2.0 with nine different GRMs for the same number of genotyped animals, pedigree, and phenotype data. A five multi-trait model was used for the evaluation in this study which is the same model used in the national evaluation system. Our results show that the Hanwoo custom v1 platform is the best option for all traits, providing a mean accuracy improvement by 0.1 - 0.3%. In the case of the scaling factor, regardless of the imputation chip platform, a setting of -1 resulted in a better accuracy increased by 0.5 to 1.6% compared to the other scaling factors. In conclusion, this study revealed that Hanwoo custom v1 used as the imputation reference chip platform and a scaling factor of -0.5 can improve the accuracy of the estimated breeding value in the Hanwoo population. This information could help to improve the current evaluation system.

Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm

  • Huang, Dai-Zheng;Gong, Ren-Xi;Gong, Shu
    • Journal of Electrical Engineering and Technology
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    • 제10권1호
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    • pp.41-46
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    • 2015
  • It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).

수학적 최적화 문제를 이용한 MGA의 성능평가 및 매개변수 연구 (Performance Evaluation and Parametric Study of MGA in the Solution of Mathematical Optimization Problems)

  • 조현만;이현진;류연선;김정태;나원배;임동주
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2008년도 정기 학술대회
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    • pp.416-421
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    • 2008
  • A Metropolis genetic algorithm (MGA) is a newly-developed hybrid algorithm combining simple genetic algorithm (SGA) and simulated annealing (SA). In the algorithm, favorable features of Metropolis criterion of SA are incorporated in the reproduction operations of SGA. This way, MGA alleviates the disadvantages of finding imprecise solution in SGA and time-consuming computation in SA. It has been successfully applied and the efficiency has been verified for the practical structural design optimization. However, applicability of MGA for the wider range of problems should be rigorously proved through the solution of mathematical optimization problems. Thus, performances of MGA for the typical mathematical problems are investigated and compared with those of conventional algorithms such as SGA, micro genetic algorithm (${\mu}GA$), and SA. And, for better application of MGA, the effects of acceptance level are also presented. From numerical Study, it is again verified that MGA is more efficient and robust than SA, SGA and ${\mu}GA$ in the solution of mathematical optimization problems having various features.

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A Simple Confocal Microscopy-based Method for Assessing Sperm Movement

  • Kim, Sung Woo;Kim, Min Su;Kim, Chan-Lan;Hwang, In-Sul;Jeon, Ik Soo
    • 한국발생생물학회지:발생과생식
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    • 제21권3호
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    • pp.229-235
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    • 2017
  • In the field of reproductive medicine, assessment of sperm motility is a key factor for achieving successful artificial insemination, in vitro fertilization, or intracellular sperm injection. In this study, the motility of boar sperms was estimated using real-time imaging via confocal microscopy. To confirm this confocal imaging method, flagellar beats and whiplash-like movement angles were compared between fresh and low-temperature-preserved ($17^{\circ}C$ for 24 h) porcine sperms. Low-temperature preservation reduced the number of flagellar beats from $11.0{\pm}2.3beats/s$ (fresh sperm) to $5.7{\pm}1.8beats/s$ and increased the flagellar bending angle from $19.8^{\circ}{\pm}13.8^{\circ}$ (fresh) to $30.6^{\circ}{\pm}15.6^{\circ}$. These data suggest that sperm activity can be assessed using confocal microscopy. The observed motility patterns could be used to develop a sperm evaluation index and automated confocal microscopic sperm motility analysis techniques.

Optimal Scheme of Retinal Image Enhancement using Curvelet Transform and Quantum Genetic Algorithm

  • Wang, Zhixiao;Xu, Xuebin;Yan, Wenyao;Wei, Wei;Li, Junhuai;Zhang, Deyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2702-2719
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    • 2013
  • A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

배전계통에서 GA를 이용한 접속변경 순서 결정 방법 (Study of Connection Process in Distribution systems using Genetic Algorithm)

  • 오선;서정갑
    • 한국위성정보통신학회논문지
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    • 제6권1호
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    • pp.6-11
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    • 2011
  • 본 논문에서는 전기 배전시스템에서 부하단의 실시간 변화에 따른 배전시스템의 안정적인 운용을 가능하게 하기 위해서 유전자 알고리즘 방법을 사용한 방법에 대해서 연구하였다 배전시스템의 안정적인 운용은 각각의 배전 구역에서의 안정성을 향상시킨다는 중요한 장점을 가지고 있다 본 논문에서는 배전계통에서 가장 어려운 것으로 평가되는 접속절차에 대한 접근을 기반의 신뢰성 모델에 기초하여 수행하였다 유전자 알고리즘은 일반적인 생물계에서의 생존을 위한 진화의 과정을 구현한 것으로서 본 논문에서는 개의 노드와 개의 배전영역을 갖는 배전시스템을 대상으로 유전자 알고리즘을 적용한 배전시스템 최적화를 구현하였다.

Aging Analysis and Reconductoring of Overhead Conductors for Radial Distribution Systems Using Genetic Algorithm

  • Legha, Mahdi Mozaffari;Mohammadi, Mohammad
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.2042-2048
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    • 2014
  • In medium voltage electrical distribution networks, reforming the loss reduction is important, and in line with this, the issue of system engineering and use of proper equipment Expansion of distribution systems results in higher system losses and poor voltage regulation. Therefore, an efficient and effective distribution system has become more important. So, proper selection of conductors in the distribution system is crucial as it determines the current density and the resistance of the line. Evaluation of aging conductors for losses and costs imposed in addition to the careful planning of technical and economic networks can be identified in the network design. In this paper the use of imperialist competitive algorithm; genetic algorithm; is proposed to optimal branch conductor selection and reconstruction in radial distribution systems planning. The objective is to minimize the overall cost of annual energy losses and depreciation on the cost of conductors to improve productivity given the maximum current carrying capacity and acceptable voltage levels. Simulations are carried out on 69-bus radial distribution network using genetic algorithm approaches to show the accuracy as well as the efficiency of the proposed solution technique.

Association of Length of Pregnancy with Other Reproductive Traits in Dairy Cattle

  • Nogalski, Zenon;Piwczynski, Dariusz
    • Asian-Australasian Journal of Animal Sciences
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    • 제25권1호
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    • pp.22-27
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    • 2012
  • The experiment involved observations of 2,514 Holstein-Friesian cows to determine the effects of environmental factors (cow's age, calving season, weight and sex of calves, housing system) and genetic factors on gestation length in dairy cattle and the correlation between gestation length and other reproductive traits (calving ease, stillbirth rates and placental expulsion). Genetic parameters were estimated based on the sires of calved cows (indirect effect) and the sires of live-born calves (direct effect). The following factors were found to contribute to prolonged gestation: increasing cow's age, male fetuses and growing fetus weight. Optimal gestation length was determined in the range of 275-277 days based on calving ease and stillbirth rates. The heritability of gestation length was estimated at 0.201-0.210 by the direct effect and 0.055-0.073 by the indirect effect. The resulting genetic correlations suggest that the efforts to optimize (prolong) gestation length could exert an adverse influence on the breeding value of bulls by increasing perinatal mortality and calving difficulty. The standard errors of the investigated parameters were relatively high, suggesting that any attempts to modify gestation length for the purpose of improving calving ease and reducing stillbirth rates should be introduced with great caution.

분산 유전자 알고리즘을 이용한 컬러 이미지의 영역분할 (Region Segmentation of a Color Image using a Distributed Genetic Algorithm)

  • 조찬윤;김상균
    • 한국멀티미디어학회논문지
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    • 제3권5호
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    • pp.470-478
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    • 2000
  • 컬러 영상들은 응용 분야별로 독특한 특성을 가지고 있다. 따라서 실용적인 영상 분할 시스템을 구축하기 위해서는 특정 영상에 독립적인 방법을 개발할 필요가 있다. 본 논문에서는 분산 유전자 알고리즘을 이용한 컬러 유방암조직 영상의 분할 방법을 제안한다. 컬러 유방암조직영상에서 양성 세포핵과 음성 세포핵을 분할하기 위해서, 컬러 정보를 효과적으로 반영하는 개선된 평가함수 및 유전연산 기반의 분산 유전자 알고리즘을 이용한다. 또한 성능 향상을 위하여 영상에서의 대표색을 추출하여 초기치로 활용한다. 유효성을 입증하기 위한 실험에서 안정된 분할 결과를 보였으며 이는 제안한 방법이 제한된 컬러를 가진 제한된 개체를 분할할 때 실용화 할 수 있음을 제시한다.

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난이도 균일성을 고려한 유전자 알고리즘 기반 평가지 생성 시스템의 설계 및 구현 (Design and Implementation of Genetic Test-Sheet-Generating Algorithm Considering Uniformity of Difficulty)

  • 송봉기;우종호
    • 한국멀티미디어학회논문지
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    • 제10권7호
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    • pp.912-922
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    • 2007
  • 원격교육 시스템의 평가 시스템에서 평가의 공정성을 위하여 매 평가 시 평가지의 난이도를 일정하게 유지할 수 있는 방법이 요구된다. 본 논문에서는 유전자 알고리즘 기반의 평가지 생성 알고리즘을 제안한다. 평가지의 각 문항에 대한 난이도가 제출자에 의해서 지정되는 기존의 방법과는 달리 제안한 알고리즘에서는 각 문항의 난이도가 학생들의 평가 결과에 따라 적응적으로 조절되고, 평가지의 평균 난이도를 일정한 수준으로 유지할 수 있다. 제안한 알고리즘에서는 평가지에 동일한 문항이 중복으로 포함되는 것을 배제하고, 이전 평가의 결과를 반영하여 적응적으로 난이도가 조절될 수 있는 새로운 형태의 유전 연산자를 설계하고 구현한다. 그리고 모의실험을 통해 기존의 임의선택 방법과 모의 담금질 방법에 비해 균일한 난이도를 갖는 평가지가 생성될 수 있음을 보인다.

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