• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.54-59
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• 2005

The cylindrical object are widely used as mechanical parts in the manufacturing process. In order to handling those objects using a robot or an automated machine automatically, the pose of the object must be known. The pose can be described by two rotation angles; one angle about the x axis and the other about the y axis. In the many previous researches these angles were obtained by the computationally intensive algorithm, that is, fitting the data as a polynomial and doing pseudo inverse. So that, this method required high performance microprocessor. In this paper in order to avoid complex computation, a new method based on a genetic algorithm is proposed and analyzed through a series of simulations. This algorithm utilized the geometry of the cylindrical shape. The simulation results show that this method find the pose angles very well In most cases, but the computation time is randomly changed because the genetic algorithm is basically one of the random search method.

• Molecules and Cells
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• v.40 no.11
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• pp.814-822
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• 2017

Meiotic homologous recombination generates new combinations of preexisting genetic variation and is a crucial process in plant breeding. Within the last decade, our understanding of plant meiotic recombination and genome diversity has advanced considerably. Innovation in DNA sequencing technology has led to the exploration of high-resolution genetic and epigenetic information in plant genomes, which has helped to accelerate plant breeding practices via high-throughput genotyping, and linkage and association mapping. In addition, great advances toward understanding the genetic and epigenetic control mechanisms of meiotic recombination have enabled the expansion of breeding programs and the unlocking of genetic diversity that can be used for crop improvement. This review highlights the recent literature on plant meiotic recombination and discusses the translation of this knowledge to the manipulation of meiotic recombination frequency and location with regards to crop plant breeding.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.123-128
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• 1995

A classical PID controller is designed by applying the GA (Genetic Algorithm) which searches the optimal parameters through three major operators of reproduction, crossover and mutation under the given constraints. The GA could minimize the designer's interference and the whole design process could easily be automated. In contrast with other traditional PID design methods which allows for the system output responses only, the design with the GA can take account of the magnitude or the rate of change of control input together with the output responses, which reflects the more realistic situations. Compared with other PIDs designed by the traditional methods such as Ziegler and analytic, the PID by the GA shows the superior response characteristics to those of others with the least control input energy.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.175-178
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-centre] in various fields. First of all, in this method, initial values are determined by the Switched Reluctance Motor of system and Ziegler-Nichols method. After deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the neural network and multiple regression model method in characteristic of output, and has extent of applying without limit of initial parameters.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.361-364
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• 2002

In this paper, we propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is $Pad'{e}$-approximated, then initial values are determined by the Ziegler-Nickels method. So deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output, and has extent of applying without limit of K, L, T parameters.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1237-1253
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• 2018

Harmony search algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and can solve different optimization problems. In order to further improve the performance of the algorithm, this paper proposes an improved harmony search algorithm. Key parameters including harmonic memory consideration (HMCR), pitch adjustment rate (PAR), and bandwidth (BW) are optimized as the number of iterations increases. Meanwhile, referring to the genetic algorithm, an improved method to generate a new crossover solutions rather than the traditional mechanism of improvisation. Four complex function optimization and pressure vessel optimization problems were simulated using the optimization algorithm of standard harmony search algorithm, improved harmony search algorithm and exploratory harmony search algorithm. The simulation results show that the algorithm improves the ability to find global search and evolutionary speed. Optimization effect simulation results are satisfactory.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.150-153
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• 2009

Anion exchange polymer electrolyte pore-filling membranes consisting of the whole hydrocarbon materials were prepared by photo polymerization with various quaternary ammonium cationic monomers and characterized on the properties for applying to solid alkali fuel cell (SAFC). Hydrocarbon porous substrates such as polyethylene were used for the preparation of the pore-filling membranes. The hydroxyl ion conductivity of the polymer electrolyte membranes prepared in this research was dependent on the composition ratio of an electrolyte monomer and crosslinking agents used for polymerization. Furthermore, these pore-filling membranes have commonly excellent properties such as smaller dimensional affects when swollen in solvents, higher mechanical strength, lower fuel crossover through the membranes, and easier preparation process than those of traditional cast membranes.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1146-1150
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, initial values are determined by the Switched Reluctance Motor of system and Ziegler-Nichols method. After deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the neural network and multiple regression model method in characteristic of output, and has extent of applying without limit of initial parameters.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.225-228
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. So deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output, and has extent of applying without limit of K, L, T parameters.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.