• 제목/요약/키워드: performance optimization

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공력 향상과 RCS 감소를 고려한 무인 전투기의 형상 최적설계 (SHAPE OPTIMIZATION OF UCAV FOR AERODYNAMIC PERFORMANCE IMPROVEMENT AND RADAR CROSS SECTION REDUCTION)

  • 조영민;최성임
    • 한국전산유체공학회지
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    • 제17권4호
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    • pp.56-68
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    • 2012
  • Nowadays, Unmanned Combat Air Vehicle(UCAV) has become an important aircraft system for the national defense. For its efficiency and survivability, shape optimization of UCAV is an essential part of its design process. In this paper, shape optimization of UCAV was processed for aerodynamic performance improvement and Radar Cross Section(RCS) reduction using Multi Objective Genetic Algorithm(MOGA). Lift and induced drag, friction drag, RCS were calculated using panel method, boundary layer theory, Physical Optics(PO) approximation respectively. In particular, calculation applied Radar Absorbing Material(RAM) was performed for the additional RCS reduction. Results are indicated that shape optimization is performed well for improving aerodynamic performance, reducing RCS. Further study will be performed with higher fidelity tools and consider other design segments including structure.

마이크로 로봇 작동 성능 향상을 위한 FEM 기반의 전자석 배치 베이지안 최적화 (FEM-based Bayesian Optimization of Electromagnet Configuration for Enhancing Microrobot Actuation)

  • 권혁진;손동훈
    • 로봇학회논문지
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    • 제19권1호
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    • pp.45-52
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    • 2024
  • This paper introduces an approach to enhance the performance of magnetic manipulation systems for microrobot actuation. A variety of eight-electromagnet configurations have been proposed to date. The previous study revealed that achieving 5 degrees of freedom (5-DOF) control necessitates at least eight electromagnets without encountering workspace singularities. But so far, the research considering the influence of iron cores embedded in electromagnets has not been conducted. This paper offers a novel approach to optimizing electromagnet configurations that effectively consider the influence of iron cores. The proposed methodology integrates probabilistic optimization with finite element methods (FEM), using Bayesian Optimization (BO). The Bayesian optimization aims to optimize the worst-case magnetic force generation for enhancing the performance of magnetic manipulation system. The proposed simulation-based model achieves approximately 20% improvement compared to previous systems in terms of actuation performance. This study has the potential for enhancing magnetic manipulation systems for microrobot control, particularly in medical and microscale technology applications.

Topology Modification을 이용한 Thomson coil Actuator의 형상 최적화 (Shape Optimization of a Thomson coil Actuator of Arc Eliminator Using Topology Modification)

  • 리웨이;정영우;고창섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.774_775
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    • 2009
  • The shape optimization of a Thomson coil actuator used in an arc eliminator is done for fast response by adopting topology modification method. The performance of the actuator is analyzed by using an equivalent circuit method. Both shape optimization and performance analysis are accomplished based on the segmentation of plate. The effectiveness of the proposed method is proved by the comparison of results before and after the shape optimization.

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잡음 환경 하에서의 입술 정보와 PSO-NCM 최적화를 통한 거절 기능 성능 향상 (Improvement of Rejection Performance using the Lip Image and the PSO-NCM Optimization in Noisy Environment)

  • 김병돈;최승호
    • 말소리와 음성과학
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    • 제3권2호
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    • pp.65-70
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    • 2011
  • Recently, audio-visual speech recognition (AVSR) has been studied to cope with noise problems in speech recognition. In this paper we propose a novel method of deciding weighting factors for audio-visual information fusion. We adopt the particle swarm optimization (PSO) to weighting factor determination. The AVSR experiments show that PSO-based normalized confidence measures (NCM) improve the rejection performance of mis-recognized words by 33%.

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A New Approach to System Identification Using Hybrid Genetic Algorithm

  • Kim, Jong-Wook;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.107.6-107
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    • 2001
  • Genetic alogorithm(GA) is a well-known global optimization algorithm. However, as the searching bounds grow wider., performance of local optimization deteriorates. In this paper, we propose a hybrid algorithm which integrates the gradient algorithm and GA so as to reinforce the performance of local optimization. We apply this algorithm to the system identification of second order RLC circuit. Identification results show that the proposed algorithm gets the better and robust performance to find the exact values of RLC elements.

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Optimizing SVM Ensembles Using Genetic Algorithms in Bankruptcy Prediction

  • Kim, Myoung-Jong;Kim, Hong-Bae;Kang, Dae-Ki
    • Journal of information and communication convergence engineering
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    • 제8권4호
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    • pp.370-376
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    • 2010
  • Ensemble learning is a method for improving the performance of classification and prediction algorithms. However, its performance can be degraded due to multicollinearity problem where multiple classifiers of an ensemble are highly correlated with. This paper proposes genetic algorithm-based optimization techniques of SVM ensemble to solve multicollinearity problem. Empirical results with bankruptcy prediction on Korea firms indicate that the proposed optimization techniques can improve the performance of SVM ensemble.

CFD를 이용한 유동제어 핀의 최적설계 (The Design Optimization of a Flow Control Fin Using CFD)

  • 위다얼;김동준
    • 대한조선학회논문집
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    • 제49권2호
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    • pp.174-181
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    • 2012
  • In this paper, the Flow Control Fin(FCF) optimization has been carried out using computational fluid dynamics(CFD) techniques. This study focused on evaluation for the performance of the FCF attached in the stern part of the ship. The main advantage of FCF is to enhance the resistance performance through the lift generation with a forward force component on the foil section, and the propulsive performance by the uniformity of velocity distribution on the propeller plane. This study intended to evaluate these functions and to find optimized FCF form for minimizing viscous resistance and equalizing wake distribution. Four parameters of FCF are used in the study, which were angle and position of FCF, longitudinal location, transverse location, and span length in the optimization process. KRISO 300K VLCC2(KVLCC2) was chosen for an example ship to demonstrate FCF for optimization. The optimization procedure utilized genetic algorithms (GAs), a gradient-based optimizer for the refinement of the solution, and Non-dominated Sorting GA-II(NSGA-II) for Multiobjective Optimization. The results showed that the optimized FCF could enhance the uniformity of wake distribution at the expense of viscous resistance.

A New Route Optimization Scheme for Network Mobility: Combining ORC Protocol with RRH and Using Quota Mechanism

  • Kong, Ruoshan;Feng, Jing;Gao, Ren;Zhou, Huaibei
    • Journal of Communications and Networks
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    • 제14권1호
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    • pp.91-103
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    • 2012
  • Network mobility (NEMO) based on mobile IP version 6 has been proposed for networks that move as a whole. Route optimization is one of the most important topics in the field of NEMO. The current NEMO basic support protocol defines only the basic working mode for NEMO, and the route optimization problem is not mentioned. Some optimization schemes have been proposed in recent years, but they have limitations. A new NEMO route optimization scheme-involving a combination of the optimized route cache protocol (ORC) and reverse routing header (RRH) and the use of a quota mechanism for optimized sessions (OwR)-is proposed. This scheme focuses on balanced performance in different aspects. It combines the ORC and RRH schemes, and some improvements are made in the session selection mechanism to avoid blindness during route optimization. Simulation results for OwR show great similarity with those for ORC and RRH. Generally speaking, the OwR's performance is at least as good as that of the RRH, and besides, the OwR scheme is capable of setting up optimal routing for a certain number of sessions, so the performance can be improved and the cost of optimal routing in nested NEMO can be decreased.

Seismic performance analysis of steel-brace RC frame using topology optimization

  • Qiao, Shengfang;Liang, Huqing;Tang, Mengxiong;Wang, Wanying;Hu, Hesong
    • Structural Engineering and Mechanics
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    • 제71권4호
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    • pp.417-432
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    • 2019
  • Seismic performance analysis of steel-brace reinforced concrete (RC) frame using topology optimization in highly seismic region was discussed in this research. Topology optimization based on truss-like material model was used, which was to minimum volume in full-stress method. Optimized bracing systems of low-rise, mid-rise and high-rise RC frames were established, and optimized bracing systems of substructure were also gained under different constraint conditions. Thereafter, different structure models based on optimized bracing systems were proposed and applied. Last, structural strength, structural stiffness, structural ductility, collapse resistant capacity, collapse probability and demolition probability were studied. Moreover, the brace buckling was discussed. The results show that bracing system of RC frame could be derived using topology optimization, and bracing system based on truss-like model could help to resolve numerical instabilities. Bracing system of topology optimization was more effective to enhance structural stiffness and strength, especially in mid-rise and high-rise frames. Moreover, bracing system of topology optimization contributes to increase collapse resistant capacity, as well as reduces collapse probability and accumulated demolition probability. However, brace buckling might weaken beneficial effects.

Energy-efficient Power Allocation based on worst-case performance optimization under channel uncertainties

  • Song, Xin;Dong, Li;Huang, Xue;Qin, Lei;Han, Xiuwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권11호
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    • pp.4595-4610
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    • 2020
  • In the practical communication environment, the accurate channel state information (CSI) is difficult to obtain, which will cause the mismatch of resource and degrade the system performance. In this paper, to account for the channel uncertainties, a robust power allocation scheme for a downlink Non-orthogonal multiple access (NOMA) heterogeneous network (HetNet) is designed to maximize energy efficiency (EE), which can ensure the quality of service (QoS) of users. We conduct the robust optimization model based on worse-case method, in which the channel gains belong to certain ellipsoid sets. To solve the non-convex non-liner optimization, we transform the optimization problem via Dinkelbach method and sequential convex programming, and the power allocation of small cell users (SCUs) is achieved by Lagrange dual approach. Finally, we analysis the convergence performance of proposed scheme. The simulation results demonstrate that the proposed algorithm can improve total EE of SCUs, and has a fast convergence performance.