• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.288-295
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• 1998

This paper proposes a new data classification method based on the tolerant rough set that extends the existing equivalent rough set. Similarity measure between two data is described by a distance function of all constituent attributes and they are defined to be tolerant when their similarity measure exceeds a similarity threshold value. The determination of optimal similarity theshold value is very important for the accurate classification. So, we determine it optimally by using the genetic algorithm (GA), where the goal of evolution is to balance two requirements such that (1) some tolerant objects are required to be included in the same class as many as possible. After finding the optimal similarity threshold value, a tolerant set of each object is obtained and the data set is grounded into the lower and upper approximation set depending on the coincidence of their classes. We propose a two-stage classification method that all data are classified by using the lower approxi ation at the first stage and then the non-classified data at the first stage are classified again by using the rough membership functions obtained from the upper approximation set. We apply the proposed classification method to the handwritten numeral character classification. problem and compare its classification performance and learning time with those of the feed forward neural network's back propagation algorithm.

• Korean Journal of Breeding Science
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• v.41 no.2
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• pp.106-114
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• 2009

In maize, knowledge of genetic diversity and genetic relationships among elite inbred lines is an significant impact on the selection of parental lines for hybrid varieties. Genetic diversity and genetic relationships among 11 parental inbred lines of Korean waxy and normal corn varieties were analyzed using 50 SSR markers distributed over the whole genome. A total of 171 allele bands were detected with an average of 3.4 alleles per locus. Number of allele bands per locus ranged from two to six and gene diversity varied from 0.165 to 0.900 with an average of 0.596 depending on the SSR loci. The cluster tree recognized three major groups with 61.6% genetic similarity. Group I includes 7 inbred lines (KL103, HW1, HW4, HW6, HW7, HW8, HW9), with similarity coefficients of between 0.616 and 0.730. Group II includes 2 inbred lines (HF1, HF2), with similarity coefficients of 0.959. Group III includes 2 inbred lines (HW3, HW5), with similarity coefficients of 0.713. The present study indicates that the SSR markers chosen for this analysis are effective for the assessment of genetic diversity and genetic relationships among 11 parental inbred lines.

• Korean Management Science Review
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• v.17 no.2
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• pp.39-54
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• 2000

This paper presents a causal forecasting model using guided genetic algorithm in continuous manufacturing process. The guide genetic algorithm(GGA) is an extended genetic algorithm(GA) using penalty function and population diversity index to increase forecasting accuracy. GGA adds to the canonical GA the concept of a penalty function to avoid selecting the unproductive chromosomes and to make a proper searching direction. Also, GGA modifies the current population using the similarity of chromosomes to avoid falling into the trap of local optimal solution. For investigation GGA performance, we used a set of real data that was collected in local glass melting processes, and experimental results show the proposed model results in the better forecasting accuracy than linear regression model and canonical GA.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.373-378
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• 2001

The optimization method based on an enhanced genetic algorithms is for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is a global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by single point method in reconstructive search space. Four numerical examples are also presented in this papers to comparing with conventional methods.

• Journal of Plant Biotechnology
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• v.5 no.4
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• pp.201-207
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• 2003

Tissue culture techniques arguably are an important approach for ex situ conservation of rare and endangered plant species. However, there is utmost importance on maintaining the genetic integrity of the introduced plants especially in tree species. To examine the genetic integrity of the micropropagated plants, we randomly screened few hardened plants of Syzygium travancoricum, a critically endangered tree taxon, using Randomly Amplified Polymorphic DNA (RAPD) markers. Twenty-three random. primers were tried and twenty-five polymorphic loci were identified. The dendrogram based on the Unweighted Pair-Group Method Arithmetic Average and Nei's similarity index depicted about 97% homology between the mother plants and micropropagated plants. Further, an attempt was made to reintroduce the micropropagated plants in the wild. Over three hundred small trees could be successfully established.

• Journal of Life Science
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• v.13 no.5
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• pp.590-595
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• 2003

The objective of this study was to assess of genetic variation within and between pumpkin species including Cucurbita maxima, C. moschata, C. pepo and C. maxima${\times}$C. moschata using RAPD markers. The 16 primers showed the amplification of 136 scorable fragments ranging from about 100 bp to 2300 bp. A total of 94 DNA fragments were polymorphic with an average 5.9 polymorphic bands per primer. A species $(C. maxima\timesC. moschata)$ has the highest number of polymorphic loci. Based on obtained data, UPGMA cluster analysis was conducted. Twenty pumpkin cultivars were classified into three large categories and identified genetic distance of cluster ranging from 0.38 and 1.00. Clustering was in accordance with the division of Curcurbitaceae into four species, C. maxima, C. moschata, C. pepo and C. $C. maxima\timesC. moschata$. Therefore, RAPD method may be essential tool for enabling discrimination of pumpkin cultivars.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• The Korean Journal of Zoology
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• v.39 no.2
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• pp.147-158
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• 1996

Since the floating goby, Choenogobius onnuloris, has intricate and diverse morphological variations, allozymic analysis at 25 loci was carried out for their populations in Korea to clarify its taxonomic status. A genetic assay carried out revealed that the floating gobies were clearly divided into three genetic groups (Tvpe-A, Tvpe-B and Tvpe-C) in Korea. Alternative alleles were fated at six loci (Aco, 6pgd, Ldh-1, Got-1, Gpf, Gp3l. Some loci had considerable heterogeneitv among three types and no evidence of gene exchange in slunpatric populations was found from statistical analyses. The genetic similarity (Rogers'S) among three types was lower than 0.80 and divergent time estimate indicates that they were speciated during 1.2-1.8 million year before present (WBP). ASso, these three types of C. unnuluris were distinguished morpholosicallv from each other by several characters such as band ornamentations. In conclusion, the evidences presented here support recognition of three types of Chuenogobius annularis as typical discrete species.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.587-592
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by simplex method in reconstructive search space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• Korean Journal of Plant Resources
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• v.32 no.3
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• pp.244-253
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• 2019

In crop breeding program, information about genetic dissimilarity on breeding resources is very important to corroborate genealogical relationships and to predict the most heterozygotic hybrid combinations and inbred breeding. This study aimed to evaluate the genetic variation in Kenyan sunflower breeding lines based on simple sequence repeat (SSR). A total of 83 alleles were detected at 32 SSR loci. The allele number per locus ranged from 2 to 7 with an average of 2.7 alleles per locus detected from the 24 sunflower accessions and the average value of polymorphic information contents (PIC) were 0.384. A cluster analysis based on the genetic similarity coefficients was conducted and the 24 sunflower breeding resources were classified into three groups. The principal coordinates (PCoA) revealed 34% and 13.38% respectively, and 47.38% of total variation. It was found that the genetic diversity within the Kenyan sunflower breeding resources was narrower than that in other sunflower germplasm resources, suggesting the importance and feasibility of introducing elite genotypes from different origins for selection of breeding lines with broader genetic base in Kenyan sunflower breeding program.