• International Journal of Korean Welding Society
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• 제3권2호
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
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• 제18권5호
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Journal of international Conference on Electrical Machines and Systems
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• 제1권1호
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• pp.135-142
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• 2012

In this paper, optimal selection of the unified power flow controller (UPFC) damping controller parameters in order to improve the power system dynamic response and its stability based on two modified intelligent algorithms have been proposed. These algorithms are based on a modified intelligent particle swarm optimization (PSO) and continuous genetic algorithm (GA). After extraction of UPFC dynamic model, intelligent PSO and genetic algorithms are used to select the effective feedback signal of the damping controller; then, to compare the performance of the proposed UPFC controller in damping the critical modes of a single-machine infinite-bus (SMIB) power system, the simulation results are presented. The comparison shows the good performance of both presented PSO and genetic algorithms in an optimal selection of UPFC damping controller parameters and damping oscillations.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• Asian-Australasian Journal of Animal Sciences
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• 제19권5호
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• pp.611-616
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• 2006

Genetic parameters for performance traits on 409 bulls and growth and carcass traits on 591 of their steer progeny were estimated in Japanese Black cattle with Gibbs sampling. Traits of bulls included body weight at the start (BWS) and finish (BWF) of test, daily gain (DG), concentrate, roughage and TDN intake, and TDN conversion ratio. Progeny traits were BWS, BWF, DG, rib eye area, marbling score (MSR), dressing percentage and subcutaneous fat thickness (SFT). In bulls, heritabilities were high for BWS (0.50) and BWF (0.63) and moderate for concentrate (0.48) and TDN intake (0.45), while in progeny, the heritability for all the studied traits was moderate to high (ranging from 0.30 to 0.73), highlighting the potential for genetic improvement of these traits. Genetic correlations between TDN intake and growth traits (BWS, BWF and DG) in bulls were highly positive (ranging from 0.77 to 0.94). The weak but negative genetic correlation (-0.20) between MSR and SFT in progeny indicated that improvement of beef marbling without increasing subcutaneous fat deposition could be possible. The estimated genetic correlations of roughage intake of bulls with body weights (BWS and BWF) and MSR of their progeny were moderate (ranging from 0.35 to 0.52). On the basis of the selection for bulls, growth traits and TDN intake correlated positively with SFT (ranging from 0.43 to 0.53) of their progeny, suggesting the necessity of controlling the increase of SFT in selection programs.

• Asian-Australasian Journal of Animal Sciences
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• 제28권9호
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• pp.1226-1234
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• 2015

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

• Asian-Australasian Journal of Animal Sciences
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• 제15권9호
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• pp.1232-1236
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• 2002

Direct and service sire genetic parameters for total number of pigs born (TNB), number of pigs born alive (NBA), total pig weight at birth (TWB), and average pig birth weight (ABW) were estimated by DF-REML under a multiple trait animal model. Data on 3,078 litters of the Yorkshire from Jan, 1975 to Dec, 1998 at National Livestock Research Institute were obtained. The animal model included fixed contemporary group effects and random additive direct, service sire, and residual effects. Additive genetic relationships among animals were included. A separate relationship matrix for service sires and their sire was also included. Additive direct heritability estimates for TNB, NBA, TWB, and ABW were 0.19, 0.18, 0.25 and 0.39, respectively. Service sire heritability estimates for TNB, NBA, TWB, and ABW were 0.02, 0.01, 0.02 and 0.01, respectively. The genetic and phenotypic correlations of TNB with NBA estimated in this study were 0.81 and 0.81, respectively, and the genetic and phenotypic correlations of TNB with TWB estimated were 0.82 and 0.76, respectively. Results indicate that service sires account for 1 to 2% of the total variation for TNB, NBA, TWB, and ABW. Further investigation is needed to determine whether the service sire effect is primarily genetic or environmental.

• 한국수산과학회지
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• 제53권4호
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• pp.544-550
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• 2020

This study was conducted to estimate the genetic improvements by selection criteria using the genetic parameters and breeding values for population of abalone Haliotis discus hannai. Genetic parameters and breeding values were estimated using all measurement data of growth traits (shell length, shell width and total weight) at 18 and 30 months old after artificial fertilization for 3,029 individuals produced in April 2014. Growth traits all exhibited moderate heritability (0.253-0.354). So it is considered that family selection will be more advantageous than individual selection. It was found that a higher genetic improvement could be expected when selecting the top 10% based on the breeding values of total weight rather than other traits. In particular, a higher genetic improvement could be expected when selecting the top 10% at 30 months old than 18 months old after artificial fertilization. This seems to be because the selection differential and heritability were higher at the 30 months old. Therefore, by estimating genetic parameters and breeding values of a population for production of the next generations by stage of growth, if they are used properly in selection and mating according to the improvement direction, it is considered that more breeding effects can be expected.

• Journal of Animal Science and Technology
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• 제55권6호
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• pp.501-508
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• 2013

This study was conducted to determine genetic correlations among carcass traits measured by ultrasound and real carcass measurements and to estimate indirect selection responses for real carcass traits based on ultrasound measurements in Hanwoo cows. To accomplish this, 22,080 ultrasound measurement records from 17,926 cows collected from 2001 to 2012 and 11,907 carcass records obtained from fattened cattle from 2008 to 2012 were used. Genetic parameters were estimated based on eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) measured by ultrasound-scanning of live cows and using the official technique on chilled bovine half-carcasses after slaughtering. Heritability and genetic correlation for carcass traits were estimated using a mixed model equation that consisted of environmental effects as fixed parameters and additive genetic effects and residual effects as random parameters, assuming that traits were different between ultrasound and carcass measurements. This statistical method was applied to the average information restricted maximum likelihood method. The heritability of EMA, BF and MS measured by ultrasound were 0.33, 0.61 and 0.46, respectively, while the heritability estimates of the corresponding traits based on carcass measurements were 0.29, 0.40 and 0.38, respectively and the genetic correlation between ultrasound and carcass traits for EMA, BF and MS were 0.41, 0.78 and 0.67, respectively. The genetic correlation between ultrasound and carcass traits was highly positive. Additionally, the selection response for marbling score was estimated to be 0.42 per generation if the cows were selected based on the ultrasound scan marbling score with an assumed selection intensity of 0.8. Overall, these results indicate that the ultrasound scan technique would be applicable to judging cow selection for genetically improved meat quality.

• Asian-Australasian Journal of Animal Sciences
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• 제19권4호
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• pp.468-474
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• 2006

Real time ultrasound data was generated on 10,596 live Hanwoo cows to study genetic variation on ultrasonic beef quality traits and to assess the best model to estimate genetic parameters on these traits. Pedigree stacking and data validation was done using the SAS statistical software and the genetic parameter estimates were obtained by EM-REML algorithm. Out of the five different multi-trait mixed animal models constructed, the optimal model included fixed effects of herd, year-season-appraisal, body condition score, linear and quadratic covariates for chest girth, the linear covariate effect of age and the random animal and residual effect of the five models studied. The heritability of longissimus muscle area (LMA), $12^{th}$ rib measurement of back fat thickness (BF) and marbling score (MS) was 0.11, 0.17 and 0.15, respectively. Genetic correlation of LMA vs. BF, LMA vs. MS and BF vs. MS was -0.15, 0.06 and 0.61, respectively. The results showed presence of genetic variation in these ultrasonic beef quality traits in Hanwoo cows and suggest that the selection of Hanwoo cows may be possible by performing ultrasonic scans on live animals, which will ultimately be helpful in reducing the generation interval and the cost of selection procedure.