• Journal of information and communication convergence engineering
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• v.3 no.4
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• pp.209-212
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• 2005

This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.98-103
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• 1995

In this paper, a method is presented for finding an optimal temperature control pattern in microwaveoven using genetic algorithm. Power spectrum of temperature variance of charcoal is obtained and oven system modeling with fuzzy-neural-network is explained. Fan on/off timing is converted to strings in gene pool and then genetic iterations make the power spectrum of simmulated temperature variance of microwave oven closer to that o charcoal.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.4
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• pp.498-504
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• 1998

This paper presents an optimal control algorithm for the overhead crane. To control the swing motion and the position tracking of the payload of the overhead crane a state feedback control algorithm is applied. by using a hybrid genetic algorithm the feedback gains of the state feedback is optimized to minimize the cost function composed of position errors and payload swing angle under unknown constant disturbances. Computer simulation is performed to demonstrate the effectiveness of the proposed control algorithm.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.428-434
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• 1997

The effect of genetic diversity in sub-populations on breeding efficiency was examined with prospect of potential crossbreeding. Simulation study of selection was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systemes; single population scheme and two population scheme. The different genetic levels were assumed to be caused by different gene frequencies. Phenotypes of two traits generated polygenic effect with additive 36 loci and residuals distributed normally were selected by selection index procedure. High genetic gain with less inbreeding was clearly recognized in the single population scheme, independently of difference in genetic level, economic weight and genetic correlation. Genetic correlation after selection in the single population scheme was lower than the two population scheme. When crossbreeding between the sub-population was taken into account, superiority of the two population scheme was suggested under those restrictions; difference in genetic level is moderate, selection criterion for the two traits is not far from even economic weight, and genetic correlation is positive with low to moderate value. The use of complementarity increased the possibility of the two population scheme.

• Korean Chemical Engineering Research
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• v.55 no.5
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• pp.652-659
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• 2017

In the present research, in order to predict activity coefficient of inorganic ions in electrolyte solution of a petroleum system, we studied 13 components in the electrolyte solution, including $H_2O$, $CO_2$ (aq), $H^+$, $Na^+$, $Ba^{2+}$, $Ca^{2+}$, $Sr^{2+}$, $Mg^{2+}$, $SO_4$, $CO_3$, $OH^-$, $Cl^-$, and $HCO_3$. To predict the activity coefficient of the components of the petroleum system (a solid/liquid equilibrium system), activity coefficient model of Extended UNIQUAC was studied, along with its adjustable parameters optimized based on a genetic algorithm. The total calculated error associated with optimizing the adjustable parameters of Extended UNIQUAC model considering the 13 components under study at three temperature levels (298.15, 323.15, and 373.15 K) using the genetic algorithm is found to be 0.07.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2042-2048
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• 2014

In medium voltage electrical distribution networks, reforming the loss reduction is important, and in line with this, the issue of system engineering and use of proper equipment Expansion of distribution systems results in higher system losses and poor voltage regulation. Therefore, an efficient and effective distribution system has become more important. So, proper selection of conductors in the distribution system is crucial as it determines the current density and the resistance of the line. Evaluation of aging conductors for losses and costs imposed in addition to the careful planning of technical and economic networks can be identified in the network design. In this paper the use of imperialist competitive algorithm; genetic algorithm; is proposed to optimal branch conductor selection and reconstruction in radial distribution systems planning. The objective is to minimize the overall cost of annual energy losses and depreciation on the cost of conductors to improve productivity given the maximum current carrying capacity and acceptable voltage levels. Simulations are carried out on 69-bus radial distribution network using genetic algorithm approaches to show the accuracy as well as the efficiency of the proposed solution technique.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.15-24
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• 2003

In this paper, an optimization model for the clustered node allocation systems in the distributed computing environment is presented. In the presented model with a distributed file system framework, the dynamics of system behavior over times is carefully thought over the nodes and hence the functionality of the cluster monitor node to check the feasibility of the current set of clustered node allocation is given. The cluster monitor node of the node allocation system capable of distributing the parallel modules to clustered nodes provides a good allocation solution using Genetic Algorithms (GA). As a part of the experimental studies, the solution quality and computation time effects of varying GA experimental parameters, such as the encoding scheme, the genetic operators (crossover, mutations), the population size, and the number of node modules, and the comparative findings are presented.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.10
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• pp.1355-1359
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• 2004

Japanese Black cattle of Hyogo prefecture (Tajima strain) are famous for its ability to produce high-quality meat and have been maintained as a closed system for more than 80 years. In order to assess the usefulness of microsatellite markers in closed cattle populations, and evaluate the genetic structure of the Tajima strain, we analyzed representative dams of the Tajima strain comprised of the substrains Nakadoi and Kinosaki. Genetic variability analyses indicated low genetic diversity in the Tajima strain. In addition, a recent genetic bottleneck, which could be accounted for by the high level of inbreeding, was detected in both substrains. In phylogenetic analyses, relationship coefficients and genetic distances between individuals were calculated using pedigree and microsatellite information. Two phylogenetic trees were constructed from microsatellite and pedigree information using the UPGMA method. Both trees illustrated that most individuals were distinguished clearly on the basis of the two substrains, although in the microsatellite tree some individuals appeared in clusters of different substrains. Comparing the two phylogenetic trees revealed good consistency between the microsatellite analysis tree and the pedigree information. The correlation coefficient between genetic distances derived from microsatellite and pedigree information was 0.686 with a high significance level (p<0.001). These results indicated that microsatellite information may provide data substantially equivalent to pedigree information even in unusually inbred herds of cattle, and suggested that microsatellite markers may be useful in revealing genetic structure without accurate or complete pedigree nformation. Japanese Black cattle of Hyogo prefecture (Tajima strain) are famous for its ability to produce high-quality meat and have been maintained as a closed system for more than 80 years. In order to assess the usefulness of microsatellite markers in closed cattle populations, and evaluate the genetic structure of the Tajima strain, we analyzed representative dams of the Tajima strain comprised of the substrains Nakadoi and Kinosaki. Genetic variability analyses indicated low genetic diversity in the Tajima strain. In addition, a recent genetic bottleneck, which could be accounted for by the high level of inbreeding, was detected in both substrains. In phylogenetic analyses, relationship coefficients and genetic distances between individuals were calculated using pedigree and microsatellite information. Two phylogenetic trees were constructed from microsatellite and pedigree information using the UPGMA method. Both trees illustrated that most individuals were distinguished clearly on the basis of the two substrains, although in the microsatellite tree some individuals appeared in clusters of different substrains. Comparing the two phylogenetic trees revealed good consistency between the microsatellite analysis tree and the pedigree information. The correlation coefficient between genetic distances derived from microsatellite and pedigree information was 0.686 with a high significance level (p<0.001). These results indicated that microsatellite information may provide data substantially equivalent to pedigree information even in unusually inbred herds of cattle, and suggested that microsatellite markers may be useful in revealing genetic structure without accurate or complete pedigree information.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.45-50
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• 2011

Recently, machine olfactory systems that have been proposed as an artificial substitute of the human olfactory system are being studied by many researchers because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. The design method adopted the sequential combination between genetic algorithms and TSK fuzzy logic system. First, the proposed method allowed the designed gas identification system effectively performing the pattern analysis because it was able to avoid the curse of dimensionality caused by use of a large number of sensors. Secondly, the method led the gas identification system to good performance because it was able to deal with drift characteristics of the sensor data by using description ability of the fuzzy system for nonlinear data. In simulation, we demonstrated the effectiveness of the designed gas identification system by using the simulation results of five types of gases.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.215-222
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• 2015

This paper sketches the strategies and designs for monitoring system of swine genetic improvement. The system should reflect every side of pig production. The system leads us to assess the efficiency of pig production and the scope of the system includes not only nucleus, multiplying and commercial herds, but also packing and processing sectors. For more accurate statistics, data for this monitoring system must be collected from all above mentioned areas, but not by random sampling. Futhermore, data analysis results including seedstocks and distribution information of genetic trend should be included in the system. The schema of knowledge database system could be employed in the system. The monitoring system in the final destination would unify the systems derived from various sources and provide any solution in swine industry including pig breeding.