• Asian-Australasian Journal of Animal Sciences
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• 제15권8호
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• pp.1085-1090
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• 2002

Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.

• 한국환경과학회지
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• 제12권10호
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• pp.1109-1116
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• 2003

The genetic algorithm is investigated fer parameters estimation of SED (storage - effective drainage) model from the Wi-stream watershed in Nakdong river basin. In the practical application of model, as a number of watershed parameters do not measure directly, it is desirable to make a good estimation from the known rainfall and runoff data. For the estimation of parameters of the SED model using the genetic algorithm, parameters of Green-Ampt equation(SM, K$\_$s/) for the estimation of an effective rainfall and initial storage(y$\_$in/) used in SED model are obtained a regression equation with 5, 10, 20 days antecedent precipitation. And as a consequence of computation, the parameters were obtained to satisfy the proposed objective function. From the comparison of observed and computed hydrographs, it shows a good agreement in the shape and the rising limb, peak, falling limb of hydrograph, so the SED model using the genetic algorithm shows a suitable model for runoff analysis in river basin.

• 한국산학기술학회논문지
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• 제18권11호
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• pp.350-356
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• 2017

국내에서는 우리 고유의 재래돼지가 보존되고 있으나 성장 및 번식능력이 낮고 등지방두께가 두꺼워 경제성이 떨어진다는 이유로 농가에서 사육을 기피하고 있다. 하지만, 나고야의정서 발효 등에 따라 고유 유전자원의 중요성은 커지고 있으며 따라서, 고유 유전자원인 재래돼지를 활용한 신 계통 개발의 중요성은 점차 커지고 있다. 본 연구는 개체모형을 이용하여 돼지의 경제적 형질에 대한 유전모수 및 유전적 변화의 추정을 통해 모체유전효과가 돼지의 경제 형질에 미치는 영향을 알아보기 위해 수행되었다. 자료는 국립축산과학원으로부터 2000년부터 2015년까지 수집한 두록종, 재래돼지 그리고 합성종(재래돼지${\times}$두록종)의 자료를 사용하였다. 본 연구에 사용된 경제형질은 일당증체량과 등지방두께를 이용하였으며 분석에 사용된 Model식은 개체효과만을 고려한 Model 1과 모체효과를 추가한 Model 2 그리고 모체 영구환경효과가 포함된 Model 3을 사용하여 분석에 이용하였다. 분석 결과 상가적 유전력이 모체효과 유전력보다 높은 유전력을 나타냈으며 상가적 유전분산과 모체 유전분산 간의 유전상관은 모든 품종에서 강한 부(-)의 상관관계를 가지는 것을 확인할 수 있었다. 따라서, 좀 더 효율적인 개량 효과를 거두기 위해서는 품종 및 형질 또는 개량 방향에 따라 개체 효과와 모체유전효과 그리고 유전상관을 적절히 고려해야 할 것으로 사료된다.

• Journal of Advanced Marine Engineering and Technology
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• 제31권3호
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• pp.293-300
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• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2002년도 춘계학술대회
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• pp.91-97
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

• 대한안전경영과학회지
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• 제4권2호
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• pp.83-101
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

• Computers and Concrete
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• 제12권2호
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• pp.109-129
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• 2013

This work presents an approach to model concrete shrinkage. The goal is to permit the concrete industry's experts to develop independent prediction models based on a reduced number of experimental data. The proposed approach combines fuzzy logic and genetic algorithm to optimize the fuzzy decision-making, thereby reducing data collection time. Such an approach was implemented for an experimental data set related to self-compacting concrete. The obtained prediction model was compared against published experimental data (not used in model development) and well-known shrinkage prediction models. The predicted results were verified by statistical analysis, which confirmed the reliability of the developed model. Although the range of application of the developed model is limited, the genetic-fuzzy approach introduced in this work proved suitable for adjusting the prediction model once additional training data are provided. This can be highly inviting for the concrete industry's experts, since they would be able to fine-tune their models depending on the boundary conditions of their production processes.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• Animal Bioscience
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• 제34권4호
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• pp.471-481
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• 2021

Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

• Journal of Animal Science and Technology
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• 제52권3호
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• pp.187-190
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• 2010

The objective of this study was to estimate genetic parameters for total number of born (TNB), number of born alive (NBA) and teat numbers (TN) of Landrace and Yorkshire breeds in Korean swine population using multiple trait animal model procedures. Total numbers of 4,653 records for teat numbers and 8,907 records for TNB and NBA collected from 2004 to 2008 on imported breeding pigs and their litter size records were used in this study. To find the appropriate model for estimation of genetic parameters (heritabilities and genetic correlations), five statistical models (two models for reproductive traits, two models for teat numbers, one model for combining these traits) considering only direct additive genetic effects, including maternal effects were used and Akaike information criteria (AIC) of each two models for reproductive traits and teat trait were compared. The means and standard deviations of TNB, NBA, and TN were $11.52{\pm}3.34$, $10.55{\pm}2.96$ and $14.30{\pm}0.83$, respectively. Estimated heritabilities for TNB and NBA traits using the model which considered only additive genetic effect were low (0.06 and 0.05, respectively). However, estimated heritabilities considering maternal genetic effects were a little bit higher than that of the model considering only additive genetic effect (0.09 for TNB and NBA, respectively). Estimated heritability for TN using the model which considered only additive genetic effect was 0.40. However, estimated heritability of direct genetic effects from a model considering maternal genetic effect was high (0.60). All results of AIC statistics, the models considering maternal effect was more appropriate than the models considering only additive genetic effect. Genetic correlations of direct additive genetic effect between litter size (TNB, NBA) and teat numbers were low (-0.18 and -0.14, respectively). However, genetic correlations of maternal effect between litter size (TNB, NBA) and teat numbers were a little bit higher than those of direct additive genetic effect (0.08 and 0.16, respectively).