• 제목/요약/키워드: unified particle swarm optimization

검색결과 8건 처리시간 0.03초

Cost effective design of RC building frame employing unified particle swarm optimization

  • Payel Chaudhuri;Swarup K. Barman
    • Advances in Computational Design
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    • 제9권1호
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    • pp.1-23
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    • 2024
  • Present paper deals with the cost effective design of reinforced concrete building frame employing unified particle swarm optimization (UPSO). A building frame with G+8 stories have been adopted to demonstrate the effectiveness of the present algorithm. Effect of seismic loads and wind load have been considered as per Indian Standard (IS) 1893 (Part-I) and IS 875 (Part-III) respectively. Analysis of the frame has been carried out in STAAD Pro software.The design loads for all the beams and columns obtained from STAAD Pro have been given as input of the optimization algorithm. Next, cost optimization of all beams and columns have been carried out in MATLAB environment using UPSO, considering the safety and serviceability criteria mentioned in IS 456. Cost of formwork, concrete and reinforcement have been considered to calculate the total cost. Reinforcement of beams and columns has been calculated with consideration for curtailment and feasibility of laying the reinforcement bars during actual construction. The numerical analysis ensures the accuracy of the developed algorithm in providing the cost optimized design of RC building frame considering safety, serviceability and constructional feasibilities. Further, Monte Carlo simulations performed on the numerical results, proved the consistency and robustness of the developed algorithm. Thus, the present algorithm is capable of giving a cost effective design of RC building frame, which can be adopted directly in construction site without making any changes.

CUDA를 이용한 Particle Swarm Optimization 구현 (Implementation of Particle Swarm Optimization Method Using CUDA)

  • 김조환;김은수;김종욱
    • 전기학회논문지
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    • 제58권5호
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    • pp.1019-1024
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    • 2009
  • In this paper, particle swarm optimization(PSO) is newly implemented by CUDA(Compute Unified Device Architecture) and is applied to function optimization with several benchmark functions. CUDA is not CPU but GPU(Graphic Processing Unit) that resolves complex computing problems using parallel processing capacities. In addition, CUDA helps one to develop GPU softwares conveniently. Compared with the optimization result of PSO executed on a general CPU, CUDA saves about 38% of PSO running time as average, which implies that CUDA is a promising frame for real-time optimization and control.

가우시안 입자 군집 최적화를 이용한 사람의 통합된 검출 및 추적 (Unified Detection and Tracking of Humans Using Gaussian Particle Swarm Optimization)

  • 안성태;김정중;이주장
    • 제어로봇시스템학회논문지
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    • 제18권4호
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    • pp.353-358
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    • 2012
  • Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method is also important as well as its accuracy. In this paper, we propose unified detection and tracking method for humans using Gaussian-PSO (Gaussian Particle Swarm Optimization) with the HOG (Histograms of Oriented Gradients) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking.

GPU의 병렬 처리 기능을 이용한 PSO(Particle Swarm Optimization) 알고리듬 구현 (Implementation of PSO(Particle Swarm Optimization) Algorithm using Parallel Processing of GPU)

  • 김은수;김조환;김종욱
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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    • pp.181-182
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    • 2008
  • 본 논문에서는 연산 최적화 알고리듬 중 PSO(Particle Swarm Optimization) 알고리듬을 NVIDIA사(社)에서 제공한 CUDA(Compute Unified Device Architecture)를 이용하여 새롭게 구현하였다. CUDA는 CPU가 아닌 GPU(Graphic Processing Unit)의 다양한 병렬 처리 능력을 사용해 복잡한 컴퓨팅 문제를 해결하는 소프트웨어 개발을 가능케 하는 기술이다. 이 기술을 연산 최적화 알고리듬 중 PSO에 적용함으로써 알고리듬의 수행 속도를 개선하였다. CUDA를 적용한 PSO 알고리듬의 검증을 위해 언어 기반으로 프로그래밍하고 다양한 Test Function을 통해 시뮬레이션 하였다. 그리고 기존의 PSO 알고리듬과 비교 분석하였다. 또한 알고리듬의 성능 향상으로 여러 가지 최적화 분야에 적용 할 수 있음을 보인다.

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Damage assessment from curvature mode shape using unified particle swarm optimization

  • Nanda, Bharadwaj;Maity, Damodar;Maiti, Dipak Kumar
    • Structural Engineering and Mechanics
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    • 제52권2호
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    • pp.307-322
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    • 2014
  • A two-step procedure to detect and quantify damages in structures from changes in curvature mode shapes is presented here. In the first step the maximum difference in curvature mode shapes of the undamaged and damaged structure are used for visual identification of the damaged internal-substructure. In the next step, the identified substructures are searched using unified particle swarm optimization technique for exact identification of damage location and amount. Efficiency of the developed procedure is demonstrated using beam like structures. This methodology may be extended for identifying damages in general frame structures.

Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market

  • Manikandan, B.V.;Raja, S. Charles;Venkatesh, P.
    • Journal of Electrical Engineering and Technology
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    • 제6권1호
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    • pp.14-24
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    • 2011
  • In order to facilitate the electricity market operation and trade in the restructured environment, ample transmission capability should be provided to satisfy the demand of increasing power transactions. The conflict of this requirement and the restrictions on the transmission expansion in the restructured electricity market has motivated the development of methodologies to enhance the available transfer capability (ATC) of existing transmission grids. The insertion of flexible AC transmission System (FACTS) devices in electrical systems seems to be a promising strategy to enhance single area ATC and multi-area ATC. In this paper, the viability and technical merits of boosting single area ATC and multi-area ATC using Thyristor controlled series compensator (TCSC), static VAR compensator (SVC) and unified power flow controller (UPFC) in single device and multi-type three similar and different device combinations are analyzed. Particle swarm optimization (PSO) algorithm is employed to obtain the optimal settings of FACTS devices. The installation cost is also calculated. The study has been carried out on IEEE 30 bus and IEEE 118 bus systems for the selected bilateral, multilateral and area wise transactions.

Power System Oscillations Damping Using UPFC Based on an Improved PSO and Genetic Algorithm

  • Babaei, Ebrahim;Bolhasan, Amin Mokari;Sadeghi, Meisam;Khani, Saeid
    • Journal of international Conference on Electrical Machines and Systems
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    • 제1권1호
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    • pp.135-142
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    • 2012
  • In this paper, optimal selection of the unified power flow controller (UPFC) damping controller parameters in order to improve the power system dynamic response and its stability based on two modified intelligent algorithms have been proposed. These algorithms are based on a modified intelligent particle swarm optimization (PSO) and continuous genetic algorithm (GA). After extraction of UPFC dynamic model, intelligent PSO and genetic algorithms are used to select the effective feedback signal of the damping controller; then, to compare the performance of the proposed UPFC controller in damping the critical modes of a single-machine infinite-bus (SMIB) power system, the simulation results are presented. The comparison shows the good performance of both presented PSO and genetic algorithms in an optimal selection of UPFC damping controller parameters and damping oscillations.

Strategy based PSO for Dynamic Control of UPFC to Enhance Power System Security

  • Mahdad, Belkacem;Bouktir, T.;Srairi, K.
    • Journal of Electrical Engineering and Technology
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    • 제4권3호
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    • pp.315-322
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    • 2009
  • Penetration and installation of a new dynamic technology known as Flexible AC Transmission Systems (FACTS) in a practical and dynamic network requires and force expert engineer to develop robust and flexible strategy for planning and control. Unified Power Flow Controller (UPFC) is one of the recent and effective FACTS devices designed for multi control operation to enhance the power system security. This paper presents a dynamic strategy based on Particle Swarm Optimization (PSO) for optimal parameters setting of UPFC to enhance the system loadability. Firstly, we perform a multi power flow analysis with load incrementation to construct a global database to determine the initial efficient bounds associated to active power and reactive power target vector. Secondly a PSO technique applied to search the new parameters setting of the UPFC within the initial new active power and reactive power target bounds. The proposed approach is implemented with Matlab program and verified with IEEE 30-Bus test network. The results show that the proposed approach can converge to the near optimum solution with accuracy, and confirm that flexible multi-control of this device coordinated with efficient location enhance the system security of power system by eliminating the overloaded lines and the bus voltage violation.