• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.460-461
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• 2006

This paper a new method which applies a genetic algorithm for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. In addition, the proposed method introduces a ultra efficient MPP tracking in a solar power generation system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.286-287
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• 2007

This paper a new method which applies a genetic algorithm for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. In addition, the proposed method introduces a ultra efficient MPP tracking in a solar power generation system.

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.290.1-290
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• 1999

No Abstract, See Full Text

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.1
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• pp.111-117
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• 2007

This paper presents a new approach to evaluate reliability indices of electric distribution systems using genetic Algorithm (GA). The use of reliability evaluation is an important aspect of distribution system planning and operation to adjust the reliability level of each area. In this paper, the reliability model is based on the optimal load transforming problem to minimize load generated load point outage in each sub-section. This approach is one of the most difficult procedures and become combination problems. A new approach using GA was developed for this problem. GA is a general purpose optimization technique based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. Test results for the model system with 24 nodes 29 branches are reported in the paper.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.252-254
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• 2006

The recent improvement in the performance of digital processor, the application of control technology, which used in the HVDC(High Voltage Direct Current) system with the digital processors, has increased. Having this research development as the basis, this paper presents an achievement of progression by tuning the parameter of PI controller based on Genetic Algorithms(GAs) and by controlling with PI controller with a developed simulator by applying the Matrix operating function, voltage source switching element, modified nodal analysis which can include transformer and the backward Euler which does not create the problem of numerical oscillation. As a result, I expect this development in the simulator HVDC System to bring more application in the field of control technology research with an expanded practicality.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.25-30
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• 2011

This paper presents a tracking vibration estimation system of the track-following system using a tracking loop gain adjustment algorithm and a genetic algorithm. The algorithms are introduced to estimate accurately the tracking vibration quantity in spite of the uncertainties of the tracking actuator. An estimated actuator model can be found by applying a genetic algorithm. Accordingly, the tracking vibration quantity can be estimated from the measured tracking error, the tracking controller and the estimated actuator model. The proposed tracking vibration estimation method is applied to the track-following system of an optical recording device and is evaluated through the experimental result.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.149-156
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• 2010

In this paper, the optimal design of a wind generator, implemented with the hybridized GA(Genetic Algorithm) and ES(Expert System), has been performed to maximize the AEP(Annual Energy Production) over the whole wind speed characterized by the statistical model of wind speed distribution. In particular, to solve the problem of calculation iterate, ES finds the superior individual and apply to initial generation of GA and it makes reduction of search domain. Meanwhile, for effective searching in reduced search domain, it propose Intelligent GA algorithm. Also, it shows the results of optimized model 500[kW] wind generator using hybridized algorithm and benchmark result of compare with GA.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.85-90
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• 2023

The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm which is well-known in Traveling Salesman Problem. This paper proposed a hybrid method based on genetic algorithm (GA) and ant colony system (ACS), called GACS, to solve traffic routing problem. In the GACS, we use genetic algorithm to optimize the ACS parameters that aims to attain the shortest trips and time through new functions to help the ants to update global and local pheromones. Our experiments are performed by the GACS framework which is developed from VANETsim with the ability of real map loading from open street map project, and updating traffic light in real-time. The obtained results show that our framework acquired higher performance than A-Star and classical ACS algorithms in terms of length of the best global tour and the time for trip.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.601-614
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• 2006

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.422-427
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• 1997

Breeding efficiency was investigated to reveal crucial factors for constructing effective breeding system with subdivided populations under equal genetic level. Simulation study of selection experiment was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systems; single population scheme and two population scheme, each of which had the same genetic parameters. Genetic correlations (-0.5 to 0.5) were assumed to be caused only by pleiotropic effect of a gene. Phenotypes of the two traits generated by polygenic effect with additive 36 loci and residuals distributed normally were selected by two traits selection index procedure. Comparing between the single population scheme and the two population scheme, the single population scheme showed higher genetic gain with lower inbreeding coefficient. This result was confirmed particularly for the situation of high selection intensity, high heritability and high degree of unevenness for economic weight. Genetic correlations in the single population scheme were significantly lower than the two population scheme when initial genetic correlation was negative. When terminal crossbreeding for the two population scheme is taken into account, superiority of the two population scheme was suggested. The terminal crossbreeding was effective under the situation of long term selection, existence of moderate inbreeding depression and use of less extreme economic weight.