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检索条件"主题词=particle swarm algorithm"

共 736 条记录，以下是51-60 订阅

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NEURAL NETWORK FORECAST UNDER THE ORGANIC HYBRID MODEL OF GENETIC algorithm AND particle swarm algorithm

NEURAL NETWORK FORECAST UNDER THE ORGANIC HYBRID MODEL OF GE...

引用

6th International Conference on Wavelet Analysis and Pattern Recognition

作者： Yang, Shu-Xia N China Elect Power Univ Beijing 102206 Peoples R China

ISBN: (纸本)9781424422388

This paper proposes a organic hybrid model of the genetic algorithm and the particle swarm algorithm firstly, then establishes the multi-factor time series forecasting model, designs the BP neural networks, adopts the organic hybrid model of genetic algorithm and particle swarm algorithm to optimize the weight from the input layer to the hidden layer, the weight from the hidden layer to the output layer and the number of neuron nodes in the hidden layer. Finally, it carries on the training with the related power consumption data in 1980-2000 in China, then obtains the network model of the nonlinear relationship between the influencing factors and the power consumption, and forecasts the electricity consumption in 2001-2005, the average absolute error rate of the forecast is 12.08%. The results show that the neural network forecasting model optimized by the organic hybrid of the genetic algorithm and the particle swarm algorithm is not precocious, and it has a high search efficiency, which also makes the accuracy of the power consumption forecast much improved. Thus, the hybrid model can be regarded as an effective method in optimizing the neural network.

关键词： Genetic algorithm particle swarm algorithm organic hybrid neural network forecast

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Coordinated Multi-ramp Control Based on Stratification Structure and particle swarm algorithm

Coordinated Multi-ramp Control Based on Stratification Struc...

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International Conference on Smart City and Systems Engineering (ICSCSE)

作者： Liang, Xinrong Yan, Mu Wuyi Univ Coll Informat Engn Jiangmen 529020 Guangdong Peoples R China South China Univ Technol Coll Automat Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781509055302

To further enrich highway ramp metering methods and enhance the control performance, a coordinated multi-ramp control method based on stratification structure and improved particle swarm algorithm (PSA) is proposed. Firstly, a cell transmission model (CTM) to describe the evolution process of highway traffic flow is formulated. Then, the system structure is designed. Moreover, the tasks of a coordinated control layer and direct control layers are determined. In the direct control layer, proportional-integral-differential (PID) controller is employed to implement control. Also, PSA is used to optimize the PID parameters. The optimization ability is improved by changing the inertia weight values and utilizing simulated annealing algorithms. Simulation example indicates that the control system can effectively eliminate congestion and maintain the stability of highway traffic flow when there exists highway congestion.

关键词： Highway Ramp Metering Coordinated Control Cell Transmission Model Stratification Structure particle swarm algorithm

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Exponential inertia weight particle swarm algorithm for Dynamics optimization of electromechanical coupling system

Exponential inertia weight particle swarm algorithm for Dyna...

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IEEE International Conference on Intelligent Computing and Intelligent Systems

作者： Wu Jianxin Zhao WeiGuo He XiangXin Wang Rui Inner Mongolia Univ Technol Coll Mech Engn Hohhot Peoples R China

ISBN: (纸本)9781424447541

Aiming at the electromechanical coupling system dynamics optimization of spindle unit of refitted machine tool for solid rocket, the optimization modeling is presented on the basis of system differential equations The research job in the paper reveals that the global optimization efficiency can be enhanced greatly, when the weight value of the swarm particle algorithm can be changed with special exponential function So, a kind of new particle swarm algorithm, Exponential inertia weight particle swarm Optimization (EPSO), is formed by adopting exponential inertia weight function Based on above research job, the optimized design parameters of the spindle unit of refitted machine tool for solid rocket are obtained in limit time period, and the engineering problem of dynamic optimization of electromechanical system is solved successfully by the method of EPSO The results are the innovative achievements in the field of mechatronics, and have broad application prospects in the design of robots, NC machine, and electromechanical equipments

关键词： particle swarm algorithm electromechanical coupling system dynamics optimization

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A new multi-objective fully-informed particle swarm algorithm for flexible job-shop scheduling problems

A new multi-objective fully-informed particle swarm algorith...

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International Conference on Computational Intelligence and Security

作者： Jia, Zhao-hong Chen, Hua-ping Tang, Jun Univ Sci & Technol China Dept Informat Management & Decis Sci Hefei 230026 Peoples R China Anhui Univ Minist Educ Key Lab Intelligent Comp & Signal Proc Hefei 230039 Peoples R China

ISBN: (纸本)9780769530734

A novel Pareto-based multi-objective Fully-informed particle swarm algorithm (FIPS) is proposed to solve flexible job-shop problems in this paper. Firstly, the population is ranked based on Pareto optimal concept. And the neighborhood topology used in FIPS is based on the Pareto rank. Secondly, the crowding distance of individuals is computed in the same Pareto level for the secondary rank Thirdly, addressing the problem of trapping into the local optimal, the mutation operators based on the coding mechanism are introduced into our algorithm. Finally, the performance of the proposed algorithm is demonstrated by applying it to several benchmark instances and comparing the experimental results.

关键词： particle swarm algorithm encoding mechanism Job shop scheduling FLEXIBLE trapping

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Blind MIMO Channel Identification Using particle swarm algorithm

Blind MIMO Channel Identification Using Particle Swarm Algor...

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3rd International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2007)

作者： Song Tao Xu Jiadong Zhang Kai Northwestern Polytech Univ Dept Elect Engn Xian 710072 Peoples R China

ISBN: (纸本)9781424413119

Blind Channel Identification is the problem of estimating the channel impulse response function given only by the measurements of the system output. In this paper, firstly, we maximized the cost function to construct the relationship between the inverse equalizer output and the input sequences, and then we used particle swarm algorithm to get the parameters and iteratively extract the MIMO (multiple-input multiple-output) system channel impulse response *** simulation examples illustrate that the proposed algorithm can achieve higher performance when using less output samples to estimate the function parameters;even when we used lots of output samples the proposed algorithm also can get better performance than the subspace algorithm and the inverse filter algorithm.

关键词： MIMO blind identification particle swarm algorithm

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Diagnostic Strategy Optimization Based On particle swarm algorithm

Diagnostic Strategy Optimization Based On Particle Swarm Alg...

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2nd International Conference on Advanced Design and Manufacturing Engineering (ADME 2012)

作者： Zhang, Yansheng Qiao, Zhongtao Jing, Jianhui Mech Engn Coll Shijiazhuang 050003 Hebei Province Peoples R China

ISBN: (纸本)9783037855010

Fault diagnostic strategy profoundly influences diagnostic efficiency and cost. Diagnostic strategy optimization is a Non-Polynomial optimizing problem, which is a hard one. Applying conventional methods to resolving it, there are some difficulties: more complex to implementing algorithm, more time to diagnosing and more difficult to attaining global optimum. particle swarm algorithm (PSA) is a new intelligent optimization algorithm, and applied to optimizing diagnostic strategy. Function of all-in cost is constructed by state probability, isolating matrix and test cost, serving as objective function. Test sequences are directly put into particle codes. particle speeds are transformed to learning probability towards the best one in the swarm. Given proper parameters in PSA, the method can search the global optimum in a little time. At last, an example shows the approach is feasible and effective.

关键词： Diagnostic Strategy particle swarm algorithm Design for Testability Test Sequence

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A fuzzy-PID controller based on particle swarm algorithm

A fuzzy-PID controller based on particle swarm algorithm

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5th International Conference on Fuzzy Systems and Knowledge Discovery

作者： Wang, Xiao-yi Liu, Zai-wen Jiang, Yang Sun, Long-hou Beijing Technol & Business Univ Sch Informat Engn Beijing 100037 Peoples R China First Lab 63856 Unit Baicheng 137001 Peoples R China

ISBN: (纸本)9780769533056

According to the characteristics of servo control system, a kind of compound fuzzy-PID controller based on particle swarm algorithm (PSO) used for servo control system has been designed in this paper which can realize no-overshoot control under the condition of assuring certain real time and reliability. Through the simulation of one fire control servo system, the method proposed in this paper is proved to be efficient and superior.

关键词： Servo system Fuzzy-PID particle swarm algorithm real time

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Control Optimization of a Pile Driving Vessel Using Spectrum Analysis and particle swarm algorithm 36

Control Optimization of a Pile Driving Vessel Using Spectrum...

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36th Chinese Control and Decision Conference (CCDC)

作者： Lin, Meihong Shen, Wengeng Wang, Xuegang CCCC Fourth Harbor Engn Inst Co Ltd Guangzhou Peoples R China

ISBN: (纸本)9798350387780;9798350387797

In offshore construction within the field of engineering vessels, the mooring equipment is fixed using steel wire ropes. In addition, the orientation angle of the vessel, orientation angle of the mooring line, pre-tension, and mooring radius are critical factors. Most of the existing construction optimization algorithms rely on time-domain calculations that demand significant computational resources and time. In order to reduce the complexity, this paper proposes an optimization algorithm which is built based on the response spectrum analysis method and particle swarm optimization algorithm. This approach incorporates failure probability-based response spectrum analysis parameters and mooring performance optimization parameters as the objectives for optimization. This study also discusses the influence of the acting waves and wind currents in different directions on the vessel. A case study of a pile driving vessel is considered to analyze these uncertainties in allowable sea conditions. To validate the calculation method, a 12-month window feasibility analysis is conducted in the case study, while focusing on the analysis of the limiting parameters of wind, wave, and current. Moreover, the importance of vessel operations under the combined influence of wind, wave, and current is studied. The obtained results demonstrate the effectiveness of using impact analysis and particle swarm optimization algorithms to conduct construction analysis on long-term sea state data and determine the optimal control parameters.

关键词： spatial orientation control response spectrum particle swarm algorithm

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CONFIGURATION OPTIMIZATION OF CROSS WAVE PRIMARY SURFACE SHEET IN THE RECUPERATOR USING particle swarm algorithm

CONFIGURATION OPTIMIZATION OF CROSS WAVE PRIMARY SURFACE SHE...

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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Ma, T. Chen, Y. T. Zhang, D. J. Ji, Y. P. Zeng, M. Wang, Q. W. Xi An Jiao Tong Univ MOE Key Lab Thermofluid Sci & Engn Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9780791854945

Highly efficient and compact primary surface recuperators are widely used in the microturbine system. However, creep deformation may occur in the passages of the primary surface sheet due to its thin thickness and long operating time. In this paper, the stress and creep deformation of cross wave (CW) primary surface sheet operating for 40000h is numerically studied. In order to improve the creep resistance, the configuration optimization of CW primary surface sheet is carried out using the APDL language in the software ANSYS combined with additional particle swarm optimization (PSO) algorithm. With the object function of minimum creep deformation, the optimal configuration of the CW primary surface sheet is recommended. Compared with the baseline design, the von mises stress and total deformation of the optimal configuration are decreased by 55% and 41%, respectively. The results indicate that the procedure based on PSO algorithm has a significant potential to reduce the creep deformation and it is recommended to be used for configuration optimization.

关键词： creep particle swarm algorithm primary surface sheet recuperator

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WoSP: A multi-optima particle swarm algorithm

WoSP: A multi-optima particle swarm algorithm

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IEEE Congress on Evolutionary Computation

作者： Hendtlass, T Swinburne Univ Technol Ctr Intelligent Syst & Complex Proc Hawthorn Vic 3122 Australia

ISBN: (纸本)0780393635

When investigating multi-optima problems, a particle swarm algorithm should not converge on a single optima but ideally should explore many optima by continual searching. The common practice of only evaluating each particle's performance at discrete intervals can, at small computational cost, be used to adjust particle behaviour in situations where the swarm is 'settling' so as to encourage the swarm to explore further. An algorithm is proposed that, by making each wave of particles partially independent, is suitable for multi optima problems.

关键词： particle swarm optimisation search problems continual searching multioptima particle swarm algorithm tabu search particle swarm optimization particle swarm algorithm dike swarms settling

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