• 생약학회지
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• 제41권4호
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• pp.297-302
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• 2010

Lophatheri Herba is the aerial part of Lophatherum gracile Bronghiart(淡竹葉, Gramineae). 25~75 cm in length. Stem: cylindrical with nodes, empty inside, externally pale yellowish green. Leaf: dehiscent of lanceolate lamina, shrunken and rolled, 5~20 cm long, 10~35 mm wide; surface: pale green ~ yellowish green, parallel-formed with veins of square reticulate, more distinct of appearance on the lower surface. Banbusae Caulis In Taeniam is the stringy strip derived from the stem with the peeled-off epidermis of Phllostachys nigra Munro var. henosis Stapf, and Phllostachys bambusoides Siebold et Zuccarini(竹葉, Gramineae). Irregular in size and shape, thin plane ~ strip-shaped, sometimes powdery, sometimes 1~3 mm thick. Outer surface: pale green ~ yellowish green, sometimes grayish white L. gracile and P. nigra have different origins although they show similar morphologic features. We were able to distinguish between L. gracile and P. nigra which are almost indistinguishable through this study. AFLP(Amplifide Fragment Length Polymorphism) was more suitable for identifying differences between L. gracile and P. nigra in comparison with other genetic analysis using chemical analysis. Therefore. molecular biological methods are believed to be useful for discovering origins of herbal medicines.

• Journal of Computing Science and Engineering
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• 제2권3호
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• pp.274-300
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• 2008

Software testing cost can be reduced if the process of testing is automated. However, the test data generation task is still performed mostly by hand although numerous theoretical works have been proposed to automate the process of generating test data and even commercial test data generators appeared on the market. Despite prolific research reports, few attempts have been made to evaluate and characterize those techniques. Therefore, a lot of works have been proposed to automate the process of generating test data. However, there is no overall evaluation and comparison of these techniques. Evaluation and comparison of existing techniques are useful for choosing appropriate approaches for particular applications, and also provide insights into the strengths and weaknesses of current methods. This paper conducts experiments on four representative test data generation techniques and discusses the experimental results. The results of the experiments show that the genetic algorithm (GA)-based test data generation performs the best. However, there are still some weaknesses in the GA-based method. Therefore, we modify the standard GA-based method to cope with these weaknesses. The experiments are carried out to compare the standard GA-based method and two modified versions of the GA-based method.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 춘계종합학술대회
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• pp.314-317
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• 2002

본 논문에서는 디지털 가버너를 개발후 유효성 검증을 위해 성능평가를 위한 방법들을 제시하고, 현장 적용시에 발생할 수 있는 시행착오를 줄이는 방법의 일환으로 시뮬레이션을 통한 검증방법에 대해 다룬다. 유전알고리즘과 모델 조정기법에 의해 대상 모델을 동정하였고 완성된 모델과 실제시스템의 출력 데이터를 비교하여 유효성을 검증하였다. 한강수력발전소 섬진강수력발전소 2호기에 설치되어있는 기존 기계식 조속기를 개발된 디지털 조속기로 대체하여 현장에 적용하고, 제어기 파라 미터의 성능평가를 위해 테스트를 수행하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.702-705
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• 2003

Directed graph and Lindenmayer system (L-system) are two major encoding methods of representation to develop creatures in an application field of artificial life. It is difficult to structurally define real morphology using the L-systems which are a grammatical rewriting system because they represent genotype as loops, procedure calls, variables, and parameters. This paper defines a class of representations called structured directed graph and interactive genetic algorithm for automatically creating 3D flower morphology. The experimental results show that natural flower morphology can be created by the proposed method.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 1997년도 제20회 화학물질의 환경독성과 건강영향
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• pp.102-102
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• 1997

• Bulletin of the Korean Chemical Society
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• 제31권8호
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• pp.2375-2378
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• 2010

• 한국작물학회:학술대회논문집
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• 한국작물학회 2018년도 춘계학술대회
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• pp.157-157
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• 2018

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (2)
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• pp.238-240
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• 2002

진화 가능한 하드웨어의 개발은 유전자 알고리즘의 새로운 가능성을 열어주었고 이에 적합한 다양한 방법이 제시되어 왔다. 하지만 일반적인 유전자 알고리즘으로는 Genetic drift가 생기거나 지역해에 빠지는 등 한계가 있기 때문에 이를 해결하기 위한 방안으로 종분화 알고리즘이 도입되고 있다. 현재까지 다양한 종분화 알고리즘이 소개되었는데 이들은 이전의 알고리즘과 비교하였을 때 높은 다양성을 유지하면서 더 좋은 해를 찾아낸다. 이 논문에서는 진화 하드웨어상에서 이러한 종분화 알고리즘들의 장단점 및 특징을 여러 비교기준을 통해 제시한다. 실험결과 Deterministic Crowding과 Struggle GA가 가장 좋은 성능을 나타내었다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 봄 학술발표논문집 Vol.29 No.1 (B)
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• pp.298-300
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• 2002

기존의 유전자 알고리즘은 우리가 원하는 최적해를 찾기 위해서 개체 집단의 크기를 가능한 크게 유지하여야 한다. 하지만 일반적인 문제들에 있어 개체의 적합도를 평가하는 젓은 어렵기 때문에 큰 집단의 로든 개체에 대하여 적합도를 평가하는 것은 커다란 시간과 비용을 소모한다. 이에 본 논문에서는 집단의 크기를 크게 유지하되 적합도 평가 과정을 줄이는 방안으로 클러스터링에 기반한 효율적인 유전자 알고리즘을 제시하고 체계적인 평가를 한다. 9개의 벤치마크 적합도 함수에 대하여 여러 클러스터링 방법을 적용하여 실험한 결과 제안한 방법의 유용성을 확인할 수 있었다.