• 제목/요약/키워드: accelerated particle swarm optimization

검색결과 2건 처리시간 0.018초

실시간 탄도 궤적 목표물 추적을 위한 GPU 기반 병렬적 입자군집최적화 기법 (Parallelized Particle Swarm Optimization with GPU for Real-Time Ballistic Target Tracking)

  • 한윤호;이헌철;권혁훈;최원석;정보라
    • 대한임베디드공학회논문지
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    • 제17권6호
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    • pp.355-365
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    • 2022
  • This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

Laser micro-drilling of CNT reinforced polymer nanocomposite: A parametric study using RSM and APSO

  • Lipsamayee Mishra;Trupti Ranjan Mahapatra;Debadutta Mishra;Akshaya Kumar Rout
    • Advances in materials Research
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    • 제13권1호
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    • pp.1-18
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    • 2024
  • The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm2) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm2) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.