• 제목/요약/키워드: Genetic relation

검색결과 276건 처리시간 0.026초

퍼지선호관계 순서화 문제와 유전자 알고리즘 기반 해법 (A Sequencing Problem with Fuzzy Preference Relation and its Genetic Algorithm-based Solution)

  • 이건명;손봉기
    • 한국지능시스템학회논문지
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    • 제14권1호
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    • pp.69-74
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    • 2004
  • A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

주가지수 관계와 유전자 알고리즘을 이용한 주식예측 (Stock Forecasting using Stock Index Relation and Genetic Algorithm)

  • 김상호;김동현;한창희;김원일
    • 한국지능시스템학회논문지
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    • 제18권6호
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    • pp.781-786
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    • 2008
  • 이 논문에서 우리는 선형결합으로 표현된 여러 가지 주가지수의 관계를 찾아내어 주식의 등락을 예측하는 방법을 제안한다. 제안된 방법에서 중요한 점은 전체 주가지수 중에서 예측하는 지수와 관계가 있는 주가지수들을 선택하는 것과 그 주가지수의 적절한 관계를 찾아내는 것이다. 전체 주가지수와의 관계를 설정하는 것은 불가능하기 때문에 밀접한 관계가 있는 주가지수만을 이용하였고 주가지수의 관계를 찾는 방법으로 유전자 알고리즘(GA : Genetic Algorithm)을 사용하였다. 제안된 방법을 이용하여 2005년부터 2007년도까지의 실제 주가지수를 가지고 모의투자 시뮬레이션을 한 결과 모의 투자금액이 230% 증가하는 것을 확인하였다.

성장에 대한 유전적.환경적 요인의 영향 (Effect of Genetic and Environmental Factors on Growth)

  • 최민형;김덕곤;이진용
    • 대한한방소아과학회지
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    • 제24권3호
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    • pp.138-149
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    • 2010
  • Objectives: The purpose of this study is to estimate genetic and environmental factors which can effect growth, and predict final height using this factors. Methods: Correlation analysis and regression analysis were conducted between measurements of height and Genetic & environmental factors through survey from 1352 child & adolescent patients. Results: Factors which have correlation with height percentile are MPH(Mid-Parental Height), NBW(Neonatal body weight), anorexia, dyspepsia, atopic dermatitis, frequency of breakfast and quality of sleeping time. MPH has moderate relation, NBW and anorexia have fair relation, and other factors have linear but poor relation. Regression equation from factors which have correlation and height percentile has 26.9% of predictive power. Regression equation considering only genetic factor has 20.4%. MPH has the most effect on height percentile. Anorexia has more effect than NBW. Other factors also have small and similar effect. Conclusions: Height of parents has the most effect on growth, anorexia, dyspepsia, atopic dermatitis, frequency of breakfast and quality of sleeping time also has effect.

Fuzzy Relation-Based Fuzzy Neural-Networks Using a Hybrid Identification Algorithm

  • Park, Ho-Seung;Oh, Sung-Kwun
    • International Journal of Control, Automation, and Systems
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    • 제1권3호
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    • pp.289-300
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    • 2003
  • In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

요트 설계시 선형의 기하학적 특성과 성능 사이의 관련성에 관한 연구 (A Study on the Relation between Hull Geometric Characteristics and Performance in the Yacht Design)

  • 하득기;김수영;김용재
    • 한국해양공학회지
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    • 제17권6호
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    • pp.91-95
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    • 2003
  • Yacht design is significantly affected by the hull geometrical characteristics. Therefore, it is necessary to closely examine the relation between hull and performance, before considering characteristics of sea condition. In this study, Genetic Programming is used to derive a formula the relationship between hull geometric characteristics and performance. Using the formula, a new guideline is proposed to determine performance of a yacht.

RAPD를 이용한 짚신나물(Agrimonia pilosa Ledeb.) 수집종 유연관계 분석 (Analysis of Genetic Relation among Collected Landraces of Agrimonsa pilosa L. Using RAPD)

  • 이용호;최주호;정대수
    • 한국자원식물학회지
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    • 제15권3호
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    • pp.250-259
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    • 2002
  • 우리 나라 자생 짚신나물(Agrimonia pilosa Ledeb.) 수집종의 분포, 자생지의 환경 및 자생지에서의 형태적 특성조사를 실시하고, 자생종 짚신나물와 도입 짚신나물 간의 형태적 특성 및 유연관계를 연구한 결과는 다음과 같다. 1. 수집된 종 중에서 하동지역의 화개면 쌍계사와 청암면 청학동에서 수집된 2종은 다른 수집종에 비하여 유전적 거리지수가 가장 가까운 수치에서 나타나 근연관계로 나타났으며, 충북 영동읍 비탄재와 경기도 강화읍 수집종간에는 유전적 거리지수는 최대값이 같은 것으로 보아 유연관계가 있는 것으로 판단된다. 2. 경남거제에서 수집(No. 7)된 것과 충북 보은에서 수집(No. 21)된 2종이 유전적으로 가장 가깝게 나타나 지역적 차이에 의한 진화에도 다양함을 보이고 있어 수집지역의 확대와 이에 따른 체계적인 선발을 통해서 우량종의 선발도 가능할 것으로 판단된다 3.증폭된 DNA band pattern에 있어서 절편크기는 300∼21000p로 PCR로 증폭된 종 상호간의 1-F값은 평균 0.624였고, 최소값 0.365, 최대값 0.827이었으며, 2개 군으로 분리되어 유전적으로 상당한 차이가 있는 것으로 나타났다.

다중 출력을 가지는 퍼지 관계 기반 퍼지뉴럴네트워크 설계 및 최적화 (Design of Fuzzy Relation-based Fuzzy Neural Networks with Multi-Output and Its Optimization)

  • 박건준;김현기;오성권
    • 전기학회논문지
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    • 제58권4호
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    • pp.832-839
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    • 2009
  • In this paper, we introduce an design of fuzzy relation-based fuzzy neural networks with multi-output. Fuzzy relation-based fuzzy neural networks comprise the network structure generated by dividing the entire input space. The premise part of the fuzzy rules of the network reflects the relation of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions such as constant, linear, and modified quadratic. For the multi-output structure the neurons in the output layer were connected with connection weights. The learning of fuzzy neural networks is realized by adjusting connections of the neurons both in the consequent part of the fuzzy rules and in the output layer, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, learning rate and momentum coefficient are automatically optimized by using real-coded genetic algorithm. Two examples are included to evaluate the performance of the proposed network.

Co-evolutionary Genetic Algorithm for Designing and Optimaizing Fuzzy Controller

  • Byung, Jun-Hyo;Bo, Sim-Kwee
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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    • pp.354-360
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    • 1998
  • In general, it is very difficult to find optimal fuzzy rules by experience when a system is dynamical and/or complex. Futhermore proper fuzzy partitioning is not deterministic and there is no unique solution. Therefore we propose a new design method of an optimal fuzzy logic controller, that is a co-evolutionary genetic algorithm finding optimal fuzzy rule and proper membership functions at the same time. We formalize the relation between fuzzy rules and membership functions in terms of fitness. We review the typical approaching methods to co-evolutionary genetic algorithms , and then classify them by fitness relation matrix. Applications of the proposed method to a path planning problem of autonomous mobile robots when moving objects exist are presented to demonstrate the performance and effectiveness of the method.

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Assessing the ductility of moment frames utilizing genetic algorithm and artificial neural networks

  • Mazloom, Moosa;Afkar, Hossein;Pourhaji, Pardis
    • Structural Monitoring and Maintenance
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    • 제5권4호
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    • pp.445-461
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    • 2018
  • The aim of this research is to evaluate the effects of the number of spans, height of spans, number of floors, height of floors, column to beam moment of inertia ratio, and plastic joints distance of beams from columns on the ductility of moment frames. For the facility in controlling the ductility of the frames, this paper offers a simple relation instead of complex equations of different codes. For this purpose, 500 analyzed and designed frames were randomly selected, and their ductility was calculated by the use of nonlinear static analysis. The results cleared that the column-to-beam moment of inertia ratio had the highest effect on ductility, and if this relation was more than 2.8, there would be no need for using the complex relations of codes for controlling the ductility of frames. Finally, the ductility of the most frames of this research could be estimated by using the combination of genetic algorithm and artificial neural networks properly.

A Sequencing Problem with Fuzzy Preference Relation

  • Lee, Kyung--Mi;Takeshi Yamakawa;Lee, Keon-Myung
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.640-645
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    • 1998
  • A Sequencing problem is one to find an ordered sequence of some entities which maximizes (or minimize) some objective function. This paper introduces an new type of sequencing problems, named a Sequencing problem with fuzzy preference relation is previded for the evaluation of the quality of sequences, It presents how such a problem can be formulated in the point of objective function. In addition, it proposes a genetic algorithm applicable to such a sequencing problem.

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