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检索条件"主题词=Particle Swarm optimization algorithm"

共 1418 条记录，以下是841-850 订阅

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The Study of Characteristics of the Hybrid particle swarm algorithm in Solution of the Global optimization Problem 5

The Study of Characteristics of the Hybrid Particle Swarm Al...

引用

5th Mediterranean Conference on Embedded Computing (MECO)

作者： Demidova, Liliya Klyueva, Irina Pylkin, Alexander Ryazan State Radio Engn Univ Ryazan Russia

ISBN: (纸本)9781509022212

The present paper considers convergence characteristics of the particle swarm algorithm and its modification - the hybrid PSO-GS algorithm obtained under combination of the PSO algorithm and Grid Search algorithm. Comparison of quality indices of the particle swarm algorithm and the steepest descent algorithm has been carried out for evaluation of advantages of the PSO algorithm in comparison with classical optimization algorithms.

关键词： particle swarm optimization algorithm grid search algorithm hybridization solution of problems of the global unconstrained optimization

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Application of Hybrid Salp swarm optimization Method for Solving OPF Problem

Application of Hybrid Salp Swarm Optimization Method for Sol...

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International Conference on Advanced Electrical Engineering (ICAEE)

作者： Khelifi, Aboubakr Bentouati, Bachir Chettih, Saliha El Sehiemy, Ragab A. Amar Telidji Univ LMSF Lab Laghouat Algeria Univ Kafrelsheikh Dept Elect Engn Fac Engn Kafr Al Sheikh Egypt

ISBN: (纸本)9781728122205

In this paper, a new hybrid solution to the Optimal Power Flow (OPF) problem is proposed. In order to achieve this goal, a new hybrid Salp swarm algorithm (HSSA) is proposed to find the optimal frontier of OPF problem. The proposed hybrid algorithm combines the advantages of the salp swarm algorithm (SSA) and particle swarm optimization (PSO) algorithm. The proposed HSSA provides more efficient solutions even for conflict constraints. This method is applied on five objective functions called power generation cost, environmental pollution emissions, active power loss, voltage deviation and voltage stability. The tests and results of the proposed HSSA have been applied to IEEE 30 bus test system to demonstrate the high performance compared with other optimization methods in the literature. Single and bi-objectives studied cases are tested to prove the capability of the proposed HSSA compared with the original SSA and PSO as well as the existing methods in the literature.

关键词： Optimal power flow salp optimization algorithm particle swarm optimization algorithm HSSA multi-objective HSSA emission minimization enhancing voltage profile

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Short Term Load Forecasting and Early Warning of Charging Station Based on PSO-SVM

Short Term Load Forecasting and Early Warning of Charging St...

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International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)

作者： Liao Xiaoqun Kang Xiaofan Ma Li Cao Nanlan Xian Univ Sci & Technol Xian 710054 Shaanxi Peoples R China

ISBN: (纸本)9781728113074

In this paper, a short-term load forecasting model and a load early warning model for charging station based on PSO-SVM are proposed. particle swarm optimization (PSO) is used to optimize the parameters of support vector machine (SVM) model, and the PSO-SVM load forecasting model for the optimal nuclear parameters of charging station is established according to the normalized root mean square error (NRMS). On the basis of it, a load warning model of charging station is established and verified by an example. Experiments show that the short-term load forecasting model based on PSO-SVM and the load forecasting model of charging station meet the requirements of forecasting and forecasting accuracy.

关键词： Load Forecasting Optimal Kernel Parameters Support Vector Machine particle swarm optimization algorithm Load Early Warning

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Reactive Power Management of MV Distribution Grid with Inverter-based PV Distributed Generations using PSO algorithm 45

Reactive Power Management of MV Distribution Grid with Inver...

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45th Annual Conference of the IEEE Industrial Electronics Society (IECON)

作者： Moondee, Wittaya Srirattanawichaikul, Watcharin Chiang Mai Univ Dept Elect Engn Fac Engn Chiang Mai Thailand Chiang Mai Univ Grad Sch Chiang Mai Thailand Prov Elect Author Bangkok Thailand

ISBN: (纸本)9781728148786

This paper presents the reactive power management approach for a medium voltage (MV) distribution grid with inverter-based photovoltaic (PV) distributed generations using a particle swarm optimization (PSO) algorithm. The objective of this research is to control the reactive power flow to support the distribution grid and voltage regulation. The control algorithm is based on centralized reactive power management at the MV distribution grid for allocating the optimal reactive power of each PV distributed generation. The system case consists of a PV system connected to the simple radial feeders in the distributed grid. Simulation studies of the proposed system are built through MATLAB and DIgSILENT PowerFactory software. The simulation results show that the proposed control algorithm is useful for mitigating voltage rise and reverse power flow in the MV distribution grid with the PV generation systems.

关键词： Reactive power management medium voltage distribution grid inverter-based photovoltaic distributed generation voltage regulation particle swarm optimization algorithm

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A direct numerical method for solving the Foppl-Hencky equation 12

A direct numerical method for solving the Foppl-Hencky equat...

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12th International Symposium on Computational Intelligence and Design (ISCID)

作者： Zhao, Min Zhang, Xiaoping Sun, Yongping Commun Univ Zhejiang Coll Media Engn Hangzhou Peoples R China

ISBN: (纸本)9781728146522

We rewrite the Foppl-Hencky equation as an unconstrained optimization, and then solve the equation by an optimization algorithm. The optimization algorithm is constructed by combining the intelligent algorithms with an numerical algorithm for different equation. We give three numerical experiments, and the simulation results show that the Rounge-Kutta method based particle swarm optimization algorithm solves the equation very well.

关键词： Foppl-Hencky equation particle swarm optimization algorithm Runge-Kutta method

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Optimal Scheduling Method for Cogeneration System Based on Heat Storage Device

Optimal Scheduling Method for Cogeneration System Based on H...

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第32届中国控制与决策会议

作者： Zhang Xu Pang Xinfu Zhao Wenjing Liu Li Zhang Yifan Mou Zurong Key Laboratory of Energy Saving and Controlling in Power System of Liaoning Province Shenyang Institute of Engineering School of Electric Power Shenyang Institute of Engineering School of Automation Shenyang Institute of Engineering State Grid Liaocheng Electric Power Supply Company

In the north of China, the problem of wind abandonment is very serious. In order to improve the ability of wind power consumption, a cogeneration system with an electric boiler is proposed. First, the mathematical model of the minimum power generation cost of the traditional unit and the optimized model are established. Second, the model is solved by using the particle swarm optimization algorithm. In addition, a power structure of combined heat and power system（CHP） is constructed for simulation experiments. Through experimental analysis, proving the feasibility of the model. Finally, Simulation results show that making the electric boiler work in the period of wind abandonment can effectively alleviate the wind abandonment phenomenon. It also can provide more space for the wind power and enhance the wind power consumption.

关键词： Combined heat and power generation Wind abandonment Electric boiler Wind power particle swarm optimization algorithm

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A Study on Fault Diagnosis of Rotating Machinery Combined Wavelet Transform with VMD

A Study on Fault Diagnosis of Rotating Machinery Combined Wa...

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作者： Huan Zhou Hao Wang Machinery and Energy Engineering College Shanghai University of Electric Power

Effective diagnosis of rotating machinery is difficult in view of the complex structure, weak early fault signals, non-stationary and non-linear vibration signals, and low signal-to-noise ratio. In this paper, a fault diagnosis method is proposed based on particle swarm optimization(PSO) and variational modal decomposition(VMD). Firstly, wavelet packet threshold is denoised on the signal, VMD is decomposed on the reconstructed signal, and PSO is optimized on the inherent mode function(IMF) obtained from decomposition so as to determine the best IMF function. Then Hilbert transform and envelope spectrum analysis are carried out on the IMF function, and the envelope spectrum analysis result is compared with theoretical calculation frequency to finally determine the fault type. The results indicate that this method can effectively reduce noise components in signals, extract weak fault information and realize fault diagnosis.

关键词： Wavelet packet denoising VMD IMF particle swarm optimization algorithm Rotating machinery

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Application of Neural Network and particle swarm optimization algorithm in Slope Runoff and Sediment Yield Calculation

Application of Neural Network and Particle Swarm Optimizatio...

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2nd International Conference on Manufacturing Science and Engineering

作者： Huang Jun Wu Pute Zhao Xining Wang Juan NW A&F Univ Coll Water Resources & Architecture Engn Yangling 712100 Shaanxi Peoples R China

ISBN: (纸本)9783037850398

Neural network black box model for predicting the slope runoff and sediment yield and two empirical equations for calculating the slope runoff and sediment yield were established with the basis of practical field data of slope runoff and sediment amount by artificial simulated rainfall experiments. In additional, particle swarm optimization algorithm is used to inquire the empirical equation's unknown parameters based on least square method. And results show that, neural network model might represent the nonlinear relationship between runoff, sediment amount and each impact factor excellently. Furthermore, predicted results are satisfactory and its relative error mean is around 10%. Empirical equations are reasonably and reliable, its relative error mean is less than 20%. These two methods provide an operable means for such intricate research of slope runoff and sediment yield predication and calculation.

关键词： Artificial Simulated Rainfall Runoff Amount Sediment Amount Neural Network particle swarm optimization algorithm Least Square Method

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Adaptive Weighted Hybrid PSOGSA algorithm and its Application in Power System Economic Load Dispatch Problem

Adaptive Weighted Hybrid PSOGSA Algorithm and its Applicatio...

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第32届中国控制与决策会议

作者： Xingcheng Pu Longlong Zhao Chaowen Xiong Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing University of Posts and Telecommunications School of Automation Chongqing University of Posts and Telecommunications

Gravity Search algorithm（GSA） is a swarm intelligence optimization algorithm based on the gravity *** standard GSA algorithm has strong global search capability,while its convergence speed is *** particle swarm optimization（PSO） algorithm has high convergence speed and search *** on the advantages of the above two algorithms,a hybrid algorithm（PSOGSA） is proposed in this paper,and two adaptive weighted update strategies are introduced into the optimization process to improve the search accuracy of the hybrid *** the same time,we added variable mutation probability to solve the problem that particles are easily be trapped in local *** order to verify the effectiveness of the two improved hybrid algorithms,the two algorithms are applied to the power system economic load dispatch（ELD） *** generation cost optimization performance tests are computed for three groups of power systems with different unit *** simulation results show that the two adaptive weighted hybrid algorithms which are proposed in this paper can effectively reduce the generation cost of the power system.

关键词： Adaptive Weighted Power System Economic Load Dispatch Problem particle swarm optimization algorithm Gravity Search algorithm

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A Quantum particle Swam optimization algorithm with Available Transfer Capability

A Quantum Particle Swam Optimization Algorithm with Availabl...

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第十九届分布式计算及其应用国际学术研讨会

作者： Qu Liping Li Dongheng Meng Yan XUE Hai-bo Engineering Training Center of Beihua University Beihua University State Grid Jilin Electric Power Co. Ltd.Shulan power supply company Department of Electrical Engineering Jilin Institute of industrial technology Peoples Government of Jilin City

Quantum particle swarm algorithm integrated the quantum behavior with particle swarm optimization algorithm,is used to settle the majorization question of calculating available transmission *** by using the software of Matlab to IEEE-30 bus system as an example of the simulation,after comparing the simulation results with the traditional particle swarm optimization algorithm results,we dissected the optimization performance and convergence speed of the above two algorithms,and verify the effectiveness of quantum particle swarm algorithm to settle the majorization question of the available transmission capability.

关键词： available transmission capacity particle swarm optimization algorithm quantum particle swarm optimization algorithm

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