• 제목/요약/키워드: Genetic Operation

검색결과 390건 처리시간 0.03초

Genetic Algorithm을 활용한 Heat Sink 최적 설계

  • 김원곤
    • 한국CDE학회지
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    • 제21권2호
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    • pp.39-49
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    • 2015
  • This paper presents the single objective design optimization of plate-fin heat sink equipped with fan cooling system using Genetic Algorithm. The proper heat sink and fan model are selected based on the previous studies. And the thermal resistance of heat sinks and fan efficiency during operation are calculated according to specific design parameters. The objective function is combination of thermal resistance and fan efficiency which have been taken to measure the performance of the heat sink. And Decision making procedure is suggested considering life time of semiconductor and Fan Operating cost. And also Analytical Model used for optimization is validated by Fluent, Ansys 13.0 and this model give a quite reasonable and reliable design.

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유전자 알고리즘과 콤플렉스법에 의한 고성능 유압휴즈의 최적 설계 (Optimal Design of a Quick-Acting Hydraulic Fuse using Genetic Algorithm and Complex Method)

  • 이성래
    • 드라이브 ㆍ 컨트롤
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    • 제11권4호
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    • pp.32-38
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    • 2014
  • The hydraulic fuse, which responds to the suddenly increased flow on rupture of a line and shuts off the fluid flow, would prevent large spillage of liquid. The quick-acting hydraulic fuse, which is mainly composed of a poppet, a seat, and a spring, must be designed to minimize the leaked flow and to prevent high collision speed between the poppet and seat during fuse operation on a line rupture. The optimal design parameters of a quick-acting hydraulic fuse were searched using the genetic algorithm and the complex method that are kinds of constrained direct search methods. The dynamic behavior of a quick-acting hydraulic fuse was researched using computer simulations that applied the obtained optimal design parameters.

CAPP에서 공정계획 선정을 위한 유전 알고리즘 접근 (A Genetic Algorithm A, pp.oach for Process Plan Selection on the CAPP)

  • 문치웅;김형수;이상준
    • 지능정보연구
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    • 제4권1호
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    • pp.1-10
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    • 1998
  • Process planning is a very complex task and requires the dynamic informatioon of shop foor and market situations. Process plan selection is one of the main problems in the process planning. In this paper, we propose a new process plan selection model considering operation flexibility for the computer aided process planing. The model is formulated as a 0-1 integer programming considering realistic shop factors such as production volume, machining time, machine capacity, transportation time and capacity of tractors such as production volume, machining time, machine capacity, transportation time capacity of transfer device. The objective of the model is to minimize the sum of the processing and transportation time for all parts. A genetic algorithm a, pp.oach is developed to solve the model. The efficiency of the proposed a, pp.oach is verified with numerical examples.

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유전 알고리즘과 Kruskal 알고리즘을 이용한 배전계통 재구성에 관한 연구 (A Study on Distribution System Reconfiguration using GA and Kruskal Algorithm)

  • 안진오;김세호
    • 대한전기학회논문지:전력기술부문A
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    • 제49권3호
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    • pp.118-123
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    • 2000
  • This paper presents an efficient algorithm for loss reduction and load balancing by sectionalizing switch operation in large scale distribution system of radial type. We use Genetic algorithm and Kruskal algorithm to solve distribution system reconfiguration. Genetic algorithm is used to minimize objective function including loss and load balancing items. Kruskal algorithm is used to satisfy the radial condition of distribution system. The experimental results show that the proposed method has the ability to search a good solution regardless of initial configuration and size of system.

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GA를 이용한 무효전력 보상기의 협조제어 (Coordinated Control of the Reactive Power Compensator Using a Genetic Algorithm)

  • 이송근
    • 대한전기학회논문지:전력기술부문A
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    • 제52권1호
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    • pp.58-61
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    • 2003
  • A loop power system has a nonlinear characteristics. Also it is very hard to analyse through a equation if a discontinuous characteristic of the ULTC is added to a system. However, the problem which is hard to analyse by equations can acquire the useful result with what use the genetic algorithm (GA) which is a multi-point search program. In this paper, we proved through a simulation that the proposed method can reduce an operation frequency of tap changers and improving the quality of voltage of the buses by decreasing the deviation between the actual voltage and the reference voltage through the coordinated control of the ULTC that use GA in the loop power system.

A Genetic Algorithm Approach to the Frequency Assignment Problem on VHF Network of SPIDER System

  • Kwon, O-Jeong
    • 한국국방경영분석학회지
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    • 제26권1호
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    • pp.56-69
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    • 2000
  • A frequency assignment problem on time division duplex system is considered. Republic of Korea Army (ROKA) has been establishing an infrastructure of tactical communication (SPIDER) system for next generation and it will be a core network structure of system. VHF system is the backbone network of SPIDER, that performs transmission of data such as voice, text and images. So, it is a significant problem finding the frequency assignment with no interference under very restricted resource environment. With a given arbitrary configuration of communications network, we find a feasible solution that guarantees communication without interference between sites and relay stations. We formulate a frequency assignment problem as an Integer Programming model, which has NP-hard complexity. To find the assignment results within a reasonable time, we take a genetic algorithm approach which represents the solution structure with available frequency order, and develop a genetic operation strategies. Computational result shows that the network configuration of SPIDER can be solved efficiently within a very short time.

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진화 신경회로망 제어기를 이용한 도립진자 시스템의 안정화 제어에 관한 연구 (A Study on Stabilization Control of Inverted Pendulum System using Evolving Neural Network Controller)

  • 김민성;정종원;성상규;박현철;심영진;이준탁
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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    • pp.243-248
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    • 2001
  • The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Thus, in this paper, an Evolving Neural Network Controller(ENNC) without Error Back Propagation(EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC) are compared with the ones of conventional optimal controller and the conventional evolving neural network controller(CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

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Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm

  • Huang, Dai-Zheng;Gong, Ren-Xi;Gong, Shu
    • Journal of Electrical Engineering and Technology
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    • 제10권1호
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    • pp.41-46
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    • 2015
  • It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).

배전계통에서 GA를 이용한 접속변경 순서 결정 방법 (Study of Connection Process in Distribution systems using Genetic Algorithm)

  • 오선;서정갑
    • 한국위성정보통신학회논문지
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    • 제6권1호
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    • pp.6-11
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    • 2011
  • 본 논문에서는 전기 배전시스템에서 부하단의 실시간 변화에 따른 배전시스템의 안정적인 운용을 가능하게 하기 위해서 유전자 알고리즘 방법을 사용한 방법에 대해서 연구하였다 배전시스템의 안정적인 운용은 각각의 배전 구역에서의 안정성을 향상시킨다는 중요한 장점을 가지고 있다 본 논문에서는 배전계통에서 가장 어려운 것으로 평가되는 접속절차에 대한 접근을 기반의 신뢰성 모델에 기초하여 수행하였다 유전자 알고리즘은 일반적인 생물계에서의 생존을 위한 진화의 과정을 구현한 것으로서 본 논문에서는 개의 노드와 개의 배전영역을 갖는 배전시스템을 대상으로 유전자 알고리즘을 적용한 배전시스템 최적화를 구현하였다.

컨테이너 터미널의 자원 할당계획에 관한 연구 (Study on the Resource Allocation Planning of Container Terminal)

  • 장양자;장성용;양창호;박진우
    • 대한산업공학회지
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    • 제28권1호
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    • pp.14-24
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    • 2002
  • We focus on resource allocation planning in container terminal operation planning problems and present network design model and genetic algorithm. We present a network design model in which arc capacities must be properly dimensioned to sustain the container traffic. This model supports various planning aspects of container terminal and brings in a very general form. The integer programming model of network design can be extended to accommodate vertical or horizontal yard configuration by adding constraints such as restricting the sum of yard cranes allocated to a block of yards. We devise a genetic algorithm for the network design model in which genes have the form of general integers instead of binary integers. In computational experiments, it is found that the genetic algorithm can produce very good solution compared to the optimal solution obtained by CPLEX in terms of computation time and solution quality. This algorithm can be used to generate many alternatives of a resource allocation plan for the container terminal and to evaluate the alternatives using various tools such as simulation.