• Title/Summary/Keyword: 유전자알고리듬

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Stacking Sequence Design of Fiber-Metal Laminate Composites for Maximum Strength (강도를 고려한 섬유-금속 적층 복합재료의 최적설계)

  • 남현욱;박지훈;황운봉;김광수;한경섭
    • Composites Research
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    • v.12 no.4
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    • pp.42-54
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    • 1999
  • FMLC(Fiber-Metal Laminate Composites) is a new structural material combining thin metal laminate with adhesive fiber prepreg, it nearly include all the advantage of metallic materials, for example: good plasticity, impact resistance, processibility, light weight and excellent fatigue properties. This research studied the optimum design of the FMLC subject to various loading conditions using genetic algorithm. The finite element method based on the shear deformation theory was used for the analysis of FMLC. Tasi-Hill failure criterion and Miser yield criterion were taken as fitness functions of the fiber prepreg and the metal laminate, respectively. The design variables were fiber orientation angles. In genetic algorithm, the tournament selection and the uniform crossover method were used. The elitist model was also used to be effective evolution strategy and the creeping random search method was adopted in order to approach a solution with high accuracy. Optimization results were given for various loading conditions and compared with CFRP(Carbon Fiber Reinforced Plastic). The results show that the FMLC is more excellent than the CFRP in point and uniform loading conditions and it is more stable to unexpected loading because the deviation of failure index is smaller than that of CFRP.

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A Study of A Design Optimization Problem with Many Design Variables Using Genetic Algorithm (유전자 알고리듬을 이용할 대량의 설계변수를 가지는 문제의 최적화에 관한 연구)

  • 이원창;성활경
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.11
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    • pp.117-126
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    • 2003
  • GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

Joint inversion of receiver function and surface-wave phase velocity for estimation of shear-wave velocity of sedimentary layers (퇴적층들의 전단파 속도 평가를 위한 수신함수와 표면파 위상 속도의 통합 역산)

  • Kurose, Takeshi;Yamanaka, Hiroaki
    • Geophysics and Geophysical Exploration
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    • v.9 no.1
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    • pp.93-101
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    • 2006
  • In this study, we propose a joint inversion method, using genetic algorithms, to determine the shear-wave velocity structure of deep sedimentary layers from receiver functions and surface-wave phase velocity. Numerical experiments with synthetic data indicate that the proposed method can avoid the trade-off between shear-wave velocity and thickness that arises when inverting the receiver function only, and the uncertainty in deep structure from surface-wave phase velocity inversion alone. We apply the method to receiver functions obtained from earthquake records with epicentral distances of about 100 km, and Rayleigh-wave phase velocities obtained from a microtremor array survey in the Kanto Plain, Japan. The estimated subsurface structure is in good agreement with the previous results of seismic refraction surveys and deep borehole data.

Word Verification using Similar Word Information and State-Weights of HMM using Genetic Algorithmin (유사단어 정보와 유전자 알고리듬을 이용한 HMM의 상태하중값을 사용한 단어의 검증)

  • Kim, Gwang-Tae;Baek, Chang-Heum;Hong, Jae-Geun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.1
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    • pp.97-103
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    • 2001
  • Hidden Markov Model (HMM) is the most widely used method in speech recognition. In general, HMM parameters are trained to have maximum likelihood (ML) for training data. Although the ML method has good performance, it dose not take account into discrimination to other words. To complement this problem, a word verification method by re-recognition of the recognized word and its similar word using the discriminative function of the two words. To find the similar word, the probability of other words to the HMM is calculated and the word showing the highest probability is selected as the similar word of the mode. To achieve discrimination to each word the weight to each state is appended to the HMM parameter. The weight is calculated by genetic algorithm. The verificator complemented discrimination of each word and reduced the error occurred by similar word. As a result of verification the total error is reduced by about 22%

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Modified AntNet Algorithm for Network Routing (네트워크 라우팅을 위한 개선된 AntNet 알고리즘)

  • Kang, Duk-Hee;Lee, Mal-Rey
    • Journal of KIISE:Software and Applications
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    • v.36 no.5
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    • pp.396-400
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    • 2009
  • During periods of large data transmission, routing selection methods are used to efficiently manage data traffic and improve the speed of transmission. One approach in routing selection is AntNet that applies the Ant algorithm in transmissions with uniform probability. However, this approach uses random selection, which can cause excessive data transmission rates and fail to optimize data This paper presents the use of the Genetic Algorithm (GA) to efficiently route and disperse data transmissions, during periods with "unnecessary weight increases for random selection". This new algorithm for improved performance provides highly accurate estimates of the transmission time and the transmission error rate.

Dynamic Contention Window Control Algorithm Using Genetic Algorithm in IEEE 802.11 Wireless LAN Systems for Logistics Information Systems (물류 정보시스템을 위한 IEEE 802.11 무선랜 시스템에서 유전자 알고리듬을 이용한 Dynamic Contention Window 제어 알고리듬)

  • Lee, Sang-Heon;Choi, Woo-Yong;Lee, Sang-Wan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.3
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    • pp.10-19
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    • 2009
  • Wireless LAN systems have been widely implemented for supporting the wireless internet services especially in the hotspot areas such as hospitals, homes, conference rooms, and so on. Compared with wired LAN systems, wireless LAN systems have the advantages of the users' mobility support and low implementation and maintenance costs. IEEE 802.11 wireless LAN systems employ the backoff algorithm to avoid contentions among STAs when two or more STAs attempt to transmit their data frames simultaneously. The MAC efficiency can be improved if the CW values are adaptively changed according to the channel state of IEEE 802.11 wireless LANs. In this paper, a dynamic contention window control algorithm is proposed using the genetic algorithm to improve the MAC throughput of IEEE 802.11 wireless LANs.

GA Based Locomotion Method for Quadruped Robot with Waist Joint to Walk on the Slop (허리 관절을 갖는 4족 로봇의 GA 기반 경사면 보행방법)

  • Choi, Yoon-Ho;Kim, Dong-Sub;Kim, Guk-Hwa
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.11
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    • pp.1665-1674
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    • 2013
  • In this paper, we propose a genetic algorithm(GA) based locomotion method of a quadruped robot with waist joint, which makes a quadruped robot walk on the slop efficiently. In the proposed method, we first derive the kinematic model of a quadruped robot with waist joint and then set the gene and the fitness function for GA. In addition, we determine the best attitude for a quadruped robot and the landing point of a foot in the walk space, which has the optimal energy stability margin(ESM). Finally, we verify the effectiveness of the proposed method by comparing with the performance of the previous method through the computer simulations.

Enhancement Alogorithm of Portal Image using Neuo-Fuzzy (뉴로 퍼지를 이용한 포탈 영상의 개선 알고리듬의 연구)

  • 허수진;신동익
    • Journal of Biomedical Engineering Research
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    • v.21 no.5
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    • pp.527-535
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    • 2000
  • For a reliable patient set-up verification, better portal films are needed to track relevant features. Simulator films are compared with portal films as a reference image in radiotherapy planning. This shows some possibilities of the use of image information of simulator images for enhancement and restorations of portal images which are very poor in quality compared with the simulator images. This paper present an approach that combine an associative memory, a kind of artificial neural networks with fuzzy image enhancement technique using genetic algorithm which determines the fuzzy region of membership function by the use of maximum entropy principles. A higher portal image quality than conventional technique is achieved.

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Optimal Design of Hybrid Motor with HTPB/LOX for Air-Launch Vehicle (공중발사체를 위한 HTPB/LOX 하이브리드 모터의 최적설계)

  • Park, Bong-Kyo;Lee, Chang-Jin;Lee, Jae-Woo;Rhee, Ihn-Seok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.32 no.4
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    • pp.53-60
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    • 2004
  • Optimal design of the hybrid motor has been performed for the first stage of nanosat air launch vehicle using F-4E Phantom as mother plane. Selected design variables are number of ports, the initial oxidizer flux, the combustion chamber pressure, and the nozzle expansion ratio. GBM(Gradient Based Method) and GA(Genetic Algorithm) are simultaneously used to compare the versatility of each algorithm for optimal design in this problem. Also, two objective functions of motor weight, and length are treated separatedly in the optimization to study how the objective function can affect the optimal design. The design results show that the optimal design can be successfully achieved either using GBM or GA regardless of the choice of the objective function; motor weight or length. And nanosat air launch vehicle which has total mass of 704.74kg, and length of first stage 3.74m is designed.

Active Vibration Control of a Cylindrical Rod Transmitting Axial Load (축 방향 하중 전달 부재의 진동제어)

  • Choe, Seung-Ju;Park, Hyeon-Cheol;Hwang, Un-Bong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.12
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    • pp.1950-1959
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    • 2001
  • An active control of the vibration transmitted by longitudinal load in flight control system is investigated numerically. The flight control system is modeled as a finite, thin shell cylinder with constant thickness. A vibration source is generated by exterior monopole source. Distributed piezoelectric actuator is used to control of the vibration. Thin shell theory is used to formulate the numerical models. The amplitude of vibration at discrete location and power transmission are minimized by analytical optimization method. Genetic algorithm is used as numerical optimization method to search optimal actuator position and size which amplitude of vibration is minimized.