• 제목/요약/키워드: genetic system

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설계 인자와 설계 목표를 이용한 진화 설계 및 재설계 (Evolutionary Design and Re-design Using Design Parameters and Goals)

  • 이강수;이건우
    • 한국정밀공학회지
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    • 제16권11호
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    • pp.106-115
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    • 1999
  • Design parameters and goals play important roles in design. Design goals are the required functions of the design elements and explicitly expressed by design parameters. Design parameters also indicate the relations among design elements, by which constraint networks can be constructed and some useful information can be induced. In this study, the mechanical design process is assumed to be the assignment of design goals and their realization through the evolutionary refinement of the design parameters. Thus an integrated design system is proposed to support the process of assigning the design goals and refining the values of the design parameters. In the design system, a genetic engine that utilizes a genetic algorithm is installed to simulate an iterative design process, which leads to an evolutionary design. The genetic engine treats design parameters as genes and design goals as evaluation function. Re-design and design modification are facilitated by the design parameters. The re-design can be activated in the design system by using the information stored in the design parameters when design parameters or goals are changed.

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멀티-에너지 도메인 동적 시스템을 위한 본드 그래프/유전프로그래밍 기반의 자동설계 방법론 (Bond Graph/Genetic Programming Based Automated Design Methodology for Multi-Energy Domain Dynamic Systems)

  • 서기성
    • 한국지능시스템학회논문지
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    • 제16권6호
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    • pp.677-682
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    • 2006
  • 멀티-도메인 공학시스템은 전기, 기계, 유압, 열등의 구성요소를 포함하고, 시스템 구성이 복잡하여 설계에 많은 어려움을 가지고 있다. 최적의 설계를 위해서는 각 도메인에 대한 통합된 설계 방법과 자동적이고 효율적인 탐색방법이 요구된다. 본 논문은 도메인에 독립적인 모델링 도구인 본드 그래프(Bond Graph)와 대규모 공간 해의 탐색에 접합한 진화 알고리즘의 일종인 유전 프로그래밍(Genetic Programming)를 결합하여 멀티 도메인 동적시스템에 대한 디자인 해를 자동적으로 생성해주는 설계 방법을 제시하였다. 제안된 설계방법의 효용성을 입증하기 위해서 3가지 서로 다른 도메인을 가진 아나로그 필터, 전동프린터 드라이브, 에어펌프 시스템에 대한 설계 결과가 기술된다.

GA-PI제어기를 이용한 유도전동기 간접 벡터제어 시스템 (An Indirect Vector Control System of Induction Motor using Genetic Algorithm based PI Controller)

  • 이학주;권성철;성세진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 B
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    • pp.1155-1157
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    • 2002
  • This paper presents the use of a simple genetic algorithm for the tuning of a proportional-integral speed controller for an induction motor drive. The influence of population size, generation number and rate of mutation on the convergence of the genetic algorithm is investigated. On Matlab/Simulink environment, this paper proposes an optimal GA-PI controller of indirect vector control for induction motor drive system. The simulation results verify that the system has a more robust to the parameter variation than classical PI controller.

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유전알고리즘 활용한 실시간 패턴 트레이딩 시스템 프레임워크 (Conceptual Framework for Pattern-Based Real-Time Trading System using Genetic Algorithm)

  • 이석준;정석재
    • 산업경영시스템학회지
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    • 제36권4호
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    • pp.123-129
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    • 2013
  • The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.

지능형 주행 안내 시스템을 위한 유전 알고리즘에 근거한 최적 경로 탐색 알고리즘 (An optimal and genetic route search algorithm for intelligent route guidance system)

  • 최규석;우광방
    • 제어로봇시스템학회논문지
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    • 제3권2호
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    • pp.156-161
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    • 1997
  • In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

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유전 알고리즘을 이용한 강인한 $H_\infty$-QFT PSS 설계에 관한 연구 (A Study on Design of Robust $H_\infty$-QFT PSS Using Genetic Algorithm)

  • 정형환;이정필;박희철;왕용필
    • 대한전기학회논문지:전력기술부문A
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    • 제52권7호
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    • pp.371-380
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    • 2003
  • In this paper, a new design method of H$H_\infty$-Qn PSS using genetic algorithm(GA) is proposed to efficiently damp low frequency oscillations despite the uncertainties and various disturbances of power systems. The selection method of evaluation function is proposed for selecting the robust PSS parameters. All QFT boundaries are satisfied automatically and H$H_\infty$-norm is minimized simultaneously without trial and error procedure. The eigenvalues and the damping ratio of dominant oscillation mode are investigated to evaluate performance of designed controller for one machine infinite bus system. A disturbance attenuation performance is investigated through singular value bode diagram of the system. Dynamic characteristics are considered to verify robustness of the proposed PSS by means of nonlinear simulations under various disturbances for various operating conditions. The results show that the proposed PSS is more robust than conventional PSS.

The Hybrid Knowledge Integration Using the Fuzzy Genetic Algorithm

  • Kim, Myoung-Jong;Ingoo Han;Lee, Kun-Chang
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.145-154
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    • 1999
  • An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes the hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

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A Neuro-Fuzzy Approach to Integration and Control of Industrial Processes:Part I

  • 김성신
    • 한국지능시스템학회논문지
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    • 제8권6호
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    • pp.58-69
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    • 1998
  • This paper introduces a novel neuro-fuzzy system based on the polynomial fuzzy neural network(PFNN) architecture. The PFNN consists of a set of if-then rules with appropriate membership functions whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection, based on the Group Method of DAta Handling is defined to overcome the overfitting problem in the modeling procedure. The hybrid genetic optimization method, which combines a genetic algorithm and the Simplex method, is developed to increase performance even if the length of a chromosome is reduced. A novel coding scheme is presented to describe fuzzy systems for a dynamic search rang in th GA. For a performance assessment of the PFNN inference system, three well-known problems are used for comparison with other methods. The results of these comparisons show that the PFNN inference system outperforms the other methods while it exhibits exceptional robustness characteristics.

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클러스터링 컴퓨터 시스템을 이용한 병렬화 유전자 알고리즘의 효율성 증대에 대한 연구 (A Study for Improvement Effect of Paralleled Genetic Algorithm by Using Clustering Computer System)

  • 이원창;성활경;백영종
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2004년도 춘계학술대회 논문집
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    • pp.430-438
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    • 2004
  • Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to Improve computational efficiency, Paralleled GA is introduced on a clustered LINUX based personal computer system.

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분류시스템의 분류 규칙 발견을 위한 유전자 알고리즘 (Genetic Algorithm to find Classification Rule for Classifier Systems)

  • 김대희;박상호
    • 한국산업정보학회논문지
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    • 제9권4호
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    • pp.16-25
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    • 2004
  • 분류시스템은 현재의 유용한 규칙들로부터 새로운 규칙들을 만들어 가기 위해 학습하는 규칙 기반 시스템이다. 본 논문에서는 방대한 데이터베이스에서 유용한 정보를 얻는 분류시스템의 분류 규칙 발견을 위한 유전자 알고리즘 을 제안하였다. 제안된 방법을 자동차 보험문제에 적용하여 제안된 유전자 알고리즘 기반 분류시스템의 성능을 평가하였다.

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