• Title/Summary/Keyword: Adaptive Optimization

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Shape Optimization of a Thomson Coil Actuator for Fast Response Using Topology Modification

  • Li, Wei;Koh, Chang-Seop
    • Journal of Electrical Engineering and Technology
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    • v.7 no.1
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    • pp.58-63
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    • 2012
  • The shape optimization of a Thomson coil actuator used in an arc eliminator is done for fast response by adopting topology modification method. The displacement of the plate in a fixed calculation time is taken as the objective function. The objective function and contribution factor are calculated by using an adaptive equivalent circuit method which has been proved accurate and efficient. Both shape optimization and performance analysis are accomplished based on the segmentation of plate. Through the refinement of the sensitive segments a precise optimal plate shape can be obtained. The effectiveness of the proposed method is proved by the comparison of results before and after the shape optimization.

Adaptive Nulling Algorithm for Null Synthesis on the Moving Jammer Environment (이동형 재밍환경에서 널 합성을 위한 적응형 널링 알고리즘)

  • Seo, Jongwoo;Park, Dongchul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.8
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    • pp.676-683
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    • 2016
  • In this paper, an adaptive nulling algorithm which can be used to form nulls in the direction of jammer or interference signals in array antennas of single port system is proposed. The proposed adaptive algorithm does not require a priori knowledge of the incoming signal direction and can be applied to the partially adaptive arrays. This algorithm is the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation adaptive algorithm, which shows stable nulling performance adaptively even on the moving jammer environment where the incident direction of the interference signal is changing with time.

Study on Pattern Synthesis of Conformal Array Antenna Using Enhanced Adaptive Genetic Algorithm (향상된 적응형 유전 알고리즘을 이용한 컨포멀 배열 안테나의 빔 합성 연구)

  • Seong, Cheol-Min;Lee, Jae-Duk;Han, In-Hee;Ryu, Hong-Kyun;Lee, Kyu-Song;Park, Dong-Chul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.5
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    • pp.592-600
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    • 2014
  • This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

An Optimization Method for BAQ(Block Adaptive Quantization) Threshold Table Using Real SAR Raw Data (영상레이다 원시데이터를 이용한 BAQ(Block Adaptive Quantization) 최적화 방법)

  • Lim, Sungjae;Lee, Hyonik;Kim, Seyoung;Nam, Changho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.2
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    • pp.187-196
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    • 2017
  • The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

Reliability-Based Shape Optimization Under the Displacement Constraints (변위 제한 조건하에서의 신뢰성 기반 형상 최적화)

  • Oh, Young-Kyu;Park, Jae-Yong;Im, Min-Gyu;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.5
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    • pp.589-595
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    • 2010
  • This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization

  • Tejani, Ghanshyam G.;Savsani, Vimal J.;Patel, Vivek K.;Bureerat, Sujin
    • Advances in Computational Design
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    • v.2 no.4
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    • pp.313-331
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    • 2017
  • In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

Variance Reductin via Adaptive Control Variates(ACV) (Variance Reduction via Adaptive Control Variates (ACV))

  • Lee, Jae-Yeong
    • Journal of the Korea Society for Simulation
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    • v.5 no.1
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    • pp.91-106
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    • 1996
  • Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

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Lightweight Design of Shell Structures Using Adaptive Inner-Front Level Set Based Topology Optimization (AIFLS-TOP) (적응적 내부 경계 레벨셋 기반 위상최적화를 이용한 쉘 구조물의 경량화 설계)

  • Park, Kang-Soo;Youn, Sung-Kie
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.12
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    • pp.1180-1187
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    • 2007
  • In the present work, topology optimization method using adaptive inner-front level set method is presented. In the conventional level set based topology optimization method, there exists an incapability for inner-front creation during optimization process. In this regard, as a new attempt to avoid and to overcome the limitation, an inner-front creation algorithm is proposed. In the inner-front creation algorithm, the strain energy density of a structure along with volume constraint is considered. Especially, to facilitate the inner-front creation process during the optimization process, the inner-front creation map which corresponds to the discrete valued function of strain energy density is constructed. In the evolution of the level set function during the optimization process, the least-squares finite element method (LSFEM) is employed. As an application to shell structures, the lightweight design of doubly curved shell and segmented mirror is carried out.

Optimum Setting of Overcurrent Relay in Distribution Systems Using Adaptive Evolutionary Algorithm (적응진화 알고리즘을 이용한 배전계통의 과전류보호계전기 최적 정정치 결정)

  • Jeong, Hee-Myung;Park, June-Ho;Lee, Hwa-Seok;Mun, Kyeong-Jun
    • Proceedings of the KIEE Conference
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    • 2006.07a
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    • pp.252-253
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    • 2006
  • This paper presents OC relay coordination to protect distribution system by Adaptive Evolutionary Algorithm(AEA). AEA is a optimization method to overcome the problems of classical optimization. The results show that the proposed method can improve more optimum relay settings than present available methods.

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A Novel Bit Rate Adaptation using Buffer Size Optimization for Video Streaming

  • Kang, Young-myoung
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.4
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    • pp.166-172
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    • 2020
  • Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.