• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 D
• /
• pp.2451-2453
• /
• 2002

In this paper, we present an infrared sensors aided map building method for mobile robot using genetic algorithm and fuzzy logic. Existing Bayesian update model using ultrasonic sensors only has a problem of the quality of map being degraded in the wall with irregularity which is caused by the wide beam width of sonar waves and Gaussian probability distribution. In order to solve this problem we propose an improved method of map building using supplementary infrared sensors. In the method, wide beam width of sonar waves is divided by infrared sensors and probability is distributed according to infrared sensors' information using fuzzy logic and genetic algorithm.

• Molecules and Cells
• /
• 제27권1호
• /
• pp.21-37
• /
• 2009

Map-based cloning to find genes of interest, marker-assisted selection (MAS), and marker-assisted breeding (MAB) all require good genetic maps with high reproducible markers. For map construction as well as chromosome assignment, development of single copy PCR-based markers and map integration process are necessary. In this study, the 132 markers (57 STS from BAC-end sequences, 13 STS from RFLP, and 62 SSR) were newly developed as single copy type PCR-based markers. They were used together with 1830 markers previously developed in our lab to construct an integrated map with the Joinmap 3.0 program. This integrated map contained 169 SSR, 354 RFLP, 23 STS from BAC-end sequences, 6 STS from RFLP, 152 AFLP, 51 WRKY, and 99 rRAMP markers on 12 chromosomes. The integrated map contained four genetic maps of two interspecific (Capsicum annuum 'TF68' and C. chinense 'Habanero') and two intraspecific (C. annuum 'CM334' and C. annuum 'Chilsungcho') populations of peppers. This constructed integrated map consisted of 805 markers (map distance of 1858 cM) in interspecific populations and 745 markers (map distance of 1892 cM) in intraspecific populations. The used pepper STS were first developed from end sequences of BAC clones from Capsicum annuum 'CM334'. This integrated map will provide useful information for construction of future pepper genetic maps and for assignment of linkage groups to pepper chromosomes.

• 한국추진공학회지
• /
• 제10권4호
• /
• pp.54-60
• /
• 2006

본 연구에서는 실험을 통하여 획득한 데이터로부터 유전 알고리즘(Genetic Algorithms)과 스케일링기법(Scaling Method)을 이용한 하이브리드 기법(Hybrid Method)으로 압축기 성능선도를 생성하는 방법을 제안하였다. 기 수행한 연구에서 유전 알고리즘만 이용할 경우 압축기 성능선도 생성 시 서지점들과 쵸크점들을 예측하는데 불분명한 단점이 있어 기존의 구성품 성능선도 생성에 널리 사용하는 스케일링 기법을 보완적으로 이용하여 보다 정확한 압축기 성능선도를 생성하였다.

• Structural Engineering and Mechanics
• /
• 제63권2호
• /
• pp.237-249
• /
• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

• 한국작물학회지
• /
• 제46권4호
• /
• pp.341-343
• /
• 2001

Molecular markers have become fundamental tools for crop genome study. The objective of this study was to construct a genetic linkage map for cowpea with PCR-based molecular markers. Five hundred and twenty random RAPD primers were screened for parental polymorphism. Ninety RAPD markers from sixty primers was segregated in 75 F2 mapping population derived from the cross of local cultivars GSC01 and GSC02. 70 RAPD markers were found to be genetically linked and formed 11 linkage groups. Linkage map spanned 474.1 cM across all 11 linkage groups. There are six linkage groups of 40 cM or more, and five smaller linkage groups range from 4.9 to 24.8 cM. The average linkage distance between pairs of markers among all linkage groups was 6.87 cM. The number of markers per linkage group ranged from 2 to 32. The longest group 1 spans 190.6 cM, while the length of shortest group 11 is 4.9 cM. This map is further needed to be saturated with the various markers such as RFLP, AFLP, SSR and more various populations and primers. In addition, morphological markers and biochemical markers should be united to construct a comprehensive linkage map.

• 한국지능시스템학회논문지
• /
• 제15권3호
• /
• pp.330-336
• /
• 2005

이동로봇의 주행을 위한 초음파 센서 만에 의한 기존의 베이지안 지도 작성법은 초음파 센서 빔의 퍼짐 특성 등에 의해 굴곡이 많은 환경의 경우 양질의 지도가 형성되지 못한다. 이러한 문제의 개선을 위해 본 논문에서는 적외선 센서를 설치하여 초음파 센서 빔의 각 영역에서의 장애물에 대한 정보를 획득하고, 이 정보를 이용 퍼지 추론시스템에 의하여 초음파 센서에 의한 정보의 신뢰도를 구하여 베이지안 지도 작성법에 의한 결과에 융합시킴으로써 보다 정확한 환경 지도를 작성하는 방법을 제시하였다. 또한, 퍼지 추론 시스템을 최적화하기 위하여 유전 알고리즘을 사용하였다. 그리고 시뮬레이션 및 실제 실험에 의해 제안된 방법이 굴곡이 많은 환경의 경우 기존의 방법 보다 정확한 지도 작성이 가능함을 검증하였다.

• 한국콘텐츠학회논문지
• /
• 제4권4호
• /
• pp.79-87
• /
• 2004

본 연구에서는 인물영상에서 입술영역을 검출하기 위한 확률맵 기반 유전자 알고리즘을 제안한다. 하나의 최적해 탐색에 사용되었던 기존 유전자 알고리즘을 수정하여 입술과 같은 영역 검출에 부합하는 다수의 해를 얻도록 적용한다. 이를 위해 공간좌표를 의미하는 염색체로 각 개체를 표현하고, 보존구간, 세대수에 따른 부분 균일교배, 비중복 선택 등의 유전연산 방법을 도입한다. 또한 HSV 칼라공간에서 HS성분에 대한 확률맵을 제안하고, 이를 적용함으로써 유전자 알고리즘의 속성인 유사 색상에 대한 적응성을 더욱 증대한다. 실험을 통하여 제안 알고리즘의 성능을 좌우하는 주요 파라미터를 분석하였으며, 입술이외의 다른ROI(Region Of Interest)의 검출에도 유연하게 적응할 수 있음을 관찰하였다.

• 반도체디스플레이기술학회지
• /
• 제13권2호
• /
• pp.23-28
• /
• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• Journal of Crop Science and Biotechnology
• /
• 제11권1호
• /
• pp.7-12
• /
• 2008

Quantitative trait loci, a genetic concept for explaining the inheritance of non-Mendelian traits in 1940s, have been realized as particular fragments of chromosome even unique genes in most crops in 21st century. However, only very a small portion of QTL has been screened out by geneticists comparing to a great number of genes underneath the quantitative traits. These identified QTL even have been seldom used into breeding program because crop breeders may not find the QTL in their breeding populations in their field station. Several key points will be proposed to meet the challenges of QTL analysis today: a fine mapping population and the related reference genetic map, QTL evaluation in multiple environments, recognizing real QTL with small genetic effect, map integration.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 추계학술대회논문집A
• /
• pp.699-704
• /
• 2000

The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.