• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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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.

• 한국육종학회지
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• 제41권2호
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• pp.106-114
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• 2009

우리나라 찰옥수수 및 종실용 옥수수 품종들의 교배친인 11개의 자식계통의 유전적 다양성 및 계통간 유연관계를 50개의 SSR 마커를 사용하여 분석한 결과는 다음과 같다. 1. 50개의 SSR primer들은 찰옥수수 및 종실용 옥수수 품종들의 교배친인 11개 자식계통들에서 총 171개의 대립단편을 증폭시켰고, 각 SSR primer들에서 증폭된 대립단편의 수는 최소 2개에서 최대 6개의 범위로 나타나 SSR loci당 평균 3.4개가 증폭되었으며, 유전적 다양성 값은 0.165에서 0.900 수준의 값을 보여 평균 0.596 값을 나타내었다. 2. 찰옥수수 품종들의 경우 미백찰의 교배친인 HW3과 HW4 자식계통은 34개의 SSR 마커, 미백2호의 교배친인 HW3과 HW9 자식계통은 29개의 SSR 마커, 조미찰의 교배친인 HW5와 HW6 자식계통은 33개의 SSR 마커, 그리고 미흑찰의 교배친인 HW7과 HW8 자식계통은 26개의 SSR 마커들에서 각각 공우성을 나타내었다. 그러나 종실용 옥수수 품종인 강일옥의 교배친인 HF1과 HF2는 단 1개의 마커(umc1588)만 공우성이었다. 3. 11개의 자식계통들은 유전적 유사성 0.616 수준에서 크게 3개의 Group으로 구분되었다. Group I은 유전적 유사성 0.616에서 0.730 수준의 범위에서 7계통(KL103, HW1, HW4, HW6, HW7, HW8, HW9)을 포함하고 있었고, Group II는 유전적 유사성 0.959 수준에서 2계통(HF1, HF2)을 포함하고 있었으며, 그리고 Group III은 유전적 유사성 0.713 수준에서 2계통(HW3, HW5)을 포함하고 있었다. 4. 찰옥수수 품종들의 교배친 자식계통들에서의 유전적 유사성은 미백찰의 교배친인 HW3과 HW4 자식계통들 사이에서는 0.584, 미백2호의 교배친인 HW3과 HW9 자식계통들 사이에서는 0.631, 조미찰의 교배친인 HW5과 HW6 자식계통들 사이에서는 0.590, 그리고 미흑찰의 교배친인 HW7과 HW8자식계통들 사이에서는 0.631 이었다. 그리고 종실용 옥수수인 강일옥의 교배친 HF1과 HF2 자식계통은 유전적 유사성이 0.959로 매우 가까운 유연관계를 나타내었다.

• 경영과학
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• 제17권2호
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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.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.373-378
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• 2001

본 연구에서의 다봉성 함수의 최적화를 위한 향상된 유전알고리듬을 제안하였다. 이 방법은 2개의 주요 단계로 구성된다. 첫째 단계는 유전알고리듬과 함수인정기준을 이용한 전역탐색단계이다. 초기해 집단에 대한 개체군의 소속도를 함수인정기준에 따라 결정한다. 둘째 단계는 개체군과 탐색최적해 사이의 유사도를 결정하고, 재구성된 탐색공간에서 단일점 탐색법에 의해 최적해를 탐색한다. 4개의 시험함수를 이용한 수치 예에 대해 종래의 방법과의 비교를 통하여 제안된 알고리듬이 모든 전역최적해 뿐만 아니라 국부최적해도 탐색이 가능함을 확인하였다.

• Journal of Plant Biotechnology
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• 제5권4호
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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.

• 생명과학회지
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• 제13권5호
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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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• 제5권3호
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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.

• 한국동물학회지
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• 제39권2호
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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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.

• 한국자원식물학회지
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• 제32권3호
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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.