• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.153-158
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• 2004

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.45-48
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• 1996

The most research on facility layout problems ignored the actual shape of building where the activities(departments) are to be arranged. They also ignored the aisles between departments inside the building. In this paper, we present a genetic algorithm that searches a very good facility layout with horizontal aisles for two different cases with respect to the department shape. From the extensive experiments, the proposed genetic algorithm generated better layouts than the ones obtained by applying Tam's algorithm. It showed about 10% improvement of performance. We found out the best combination of genetic operators through the experiments.

• Korean Journal of Poultry Science
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• v.22 no.2
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• pp.97-104
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• 1995

Recently, DNA fingerprinting has been utilized as the most powerful tool for genetic analysis and improvement of poultry. This technique enables us to solve several problems of poultry breeding ; traits of low heritability, difficulty in keeping the performance records, measuring in late of life, and sex limited traits. Application of DNA fingerprinting is chiefly focused to individual and population identification, evolution force, quantitative trait marker, introgression of new gene, and prediction of heterosis. Thus, research work on DNA fingerprinting will he accelerated to analyze genetic components exactly and improve the performance of poultry.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1272-1274
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• 2003

In this paper, we present a new algorithm for high dimensional data reduction based on wavelet decomposition and Genetic Algorithm (GA). Comparative results show the superiority of our algorithm for dimensionality reduction and accuracy improvement.

• IE interfaces
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• v.23 no.2
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.1-8
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• 1998

This paper proposes a reinforcement genetic programming based on the reinforcement learning method for the performance improvement of genetic programming. Genetic programming which has tree structure program has much flexibility of problem expression because it has no limitation in the size of chromosome compared to the other evolutionary algorithms. But worse results on the point of convergence associated with mutation and crossover operations are often due to this characteristic. Therefore the sizes of population and maximum generation are typically larger than those of the other evolutionary algorithms. This paper proposes a new method that executes crossover and mutation operations based on reinforcement and inhibition mechanism of reinforcement learning. The validity of the proposed method is evaluated by appling it to the artificial ant problem.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.76-85
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• 1998

Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

• Journal of Power System Engineering
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• v.18 no.5
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• Journal of Animal Science and Technology
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• v.44 no.6
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• pp.685-692
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• 2002

This study was carried out to estimate the genetic correlations for the carcass and growth traits of Hanwoo bulls measured at 12 and 18 months of age on the basis of the data form 1,823 heads of Hanwoo bulls raised at the Livestock Improvement Main Center from 1991 to 1998. Genetic correlations were estimated with multiple trait animal model using MTDFREML. The genetic correlations of the body weight at 12 months with average daily gain during 6${\sim}$12 months and with the body length were 0.76 and 0.79, respectively. The genetic correlations of the body weight at 18 months with average daily gain during 6${\sim}$18 months and with the body length were 0.86 and 0.82, respectively. The genetic correlations of the carcass weight with dressing percent, eye muscle area, backfat thickness and carcass length were 0.39, 0.37, 0.44 and 0.63, respectively. And estimate of 0.36 was obtained for the genetic correlation between backfat thickness and marbling score. The high and positive genetic correlations of 0.71 and 0.96 were estimated for the carcass weight with the body weights at 12 and 18 months. The genetic correlations of the carcass weight with body lengths at 12 and 18 months were 0.63 and 0.75, respectively. Positive genetic correlations were estimated for the dressing percentage with the body weight, average daily gain, body length, thurls width and chest girth. Low genetic correlations were estimated between eye muscle area and the growth traits ranging from -0.07 to 0.32. Dressing percentage was low correlated genetically with the growth traits except for the chest girth at 18 months. The genetic correlation between marbling score and chest girth at 18 months estimated was 0.25.

• Journal of agriculture & life science
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• v.51 no.4
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• pp.111-119
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• 2017

The objective of this study is to check the applicability of the improved trait through the nutritional value of loin and the estimation of genetic parameter through the chemical composition analysis(moisture, crude fat, crude protein, crude ash) for Hanwoo carcass traits and loin. The data of 1kg of loin sampled and analyzed for 2,033 Hanwoo progeny test(steers) from $47^{th}$ to $57^{th}$ were used as the disclosure material used in this study. The study resulted that the heritability for carcass weight, eye muscle area, back fat thickness and marbling score which are Hanwoo carcass traits was estimated to be 0.37, 0.51, 0.44 and 0.57, respectively and the heritability for moisture, crude fat, crude protein and crude ash which are the chemical composition analysis to be 0.62, 0.64, 0.58 and 0.12, respectively. And the genetic correlation estimate between carcass weight and crude fat was 0.35, and marbling score with moisture, crude fat, crude protein and crude ash was -0.966, 0.964, -0.924 and -0.664, respectively. The genetic correlation between moisture and crude fat, crude protein was analyzed to be -0.998, 0.969 and a high genetic correlation was shown in crude fat and crude protein, -0.979. As the chemical composition analysis value showed high heritability in moisture, crude fat and crude protein, improved traits are considered to be available.