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

共 1415 条记录，以下是1171-1180 订阅

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Combining CA and PSO to Solve Flexible Job shop Scheduling Problem

Combining CA and PSO to Solve Flexible Job shop Scheduling P...

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26th Chinese Control and Decision Conference (CCDC)

作者： Zhou Wei Bu Yan-ping Zhou Ye-qing E China Univ Sci & Technol Sch Business Shanghai 200237 Peoples R China

ISBN: (纸本)9781479937066

The flexible job shop scheduling problem (FJSP) is an extension of the classic job shop scheduling problem (JSP), which breaks through the uniqueness of limit resources, allows a procedure in many machines processing and one machine processing many kinds of different types of procedures. It is more practical and complex than JSP. The computational complexity of FjSP is much higher, which disables exact solution methods and makes heuristic approaches more qualified. A hybrid optimization algorithm, CPSO, based on the cultural algorithm and particle swarm optimization algorithm, is proposed in this paper to solve the FJSP. The objective is to minimize makespan. Computational results show that this hybrid method is able to solve efficiently these kinds of problems.

关键词： cultural algorithm particle swarm optimization algorithm flexible job shop scheduling problem makespan

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Research on The Effect of Selection of Objective Function on optimization Results 11

Research on The Effect of Selection of Objective Function on...

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11th World Congress on Intelligent Control and Automation

作者： Xiao, Tiantian Han, Pu Hong, Bo Dong, Ze North China Elect Power Univ Hebei Engn Res Ctr Simulat & Optimized Control Po Dept Automat Baoding 071003 Peoples R China

ISBN: (纸本)9781479958252

In this paper, based on particle swarm optimization (PSO) algorithm to observe the different optimization results by changing the objective function. By comparing indicators of various types of objective function, clearly showing its intuitive respective advantages and disadvantages. Herein we can derived from the comprehensive objective function is a relatively good target function, stability, accuracy and rapidity performance can better meet the requirements of people.

关键词： particle swarm optimization algorithm Objective function Parameter optimization

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Hybrid Heuristic algorithm Based Controller Tuning for a Bioreactor

Hybrid Heuristic Algorithm Based Controller Tuning for a Bio...

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International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)

作者： Ramya, S. Latha, K. Anna Univ Madras Inst Technol Dept Instrumentat Engn Madras 600025 Tamil Nadu India

ISBN: (纸本)9781479949816

Bioreactor is one of the prime processing units widely employed to produce important chemical and biochemical compounds. In this paper, a hybrid heuristic algorithm has been attempted to tune PID controller for nonlinear Bioreactor model. The hybrid algorithm is a combination of Bacterial Foraging optimization (BFO) and particle swarm optimization (PSO) algorithm. Multiobjective performance indexes such as Integral Square Error, peak overshoot are considered to guide this algorithm for discovering best possible value of controller parameters. The controller tuning procedure is individually discussed for both stable and unstable steady state operating region of simulated bio-reactor model. The effectiveness of the proposed scheme has been validated through a comparative study with BFO, PSO based controller tuning methods proposed in the literature. The results show that, the hybrid method provides improved performance in reference tracking and load disturbance rejection with minimal ISE value.

关键词： Bioreactor Bacterial Foraging Optimisation algorithm particle swarm optimization algorithm PID controller

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Improved particle swarm algorithm with Dynamic Adjustment basing on Velocity Information 10

Improved Particle Swarm Algorithm with Dynamic Adjustment ba...

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10th International Conference on Natural Computation (ICNC)

作者： Chen, Zhuo Liang, Ximing Beijing Univ Civil Engn & Architecture Sch Sci Beijing Peoples R China

ISBN: (纸本)9781479951512

particle swarm optimization algorithm is a simple and effective modern optimization algorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence proposed. In the iteration of the proposed algorithm, the particles are distinguished to be active or stable according to their velocity information. For the active particles, to maintain the diversity of population, they are replaced by selection from its previous generation's position and its reverse point, which combines the strategy of opposition-based learning. While for the stable particles, to enhance the convergence speed and increase the local search capability, they are improved by conjugate gradient method. The proposed improved PSO algorithm has come through numerical experiments of classic test functions. The results showed that, compared with other improved algorithms, this proposed improved PSO algorithm is feasible and effective.

关键词： particle swarm optimization algorithm conjugate gradient algorithm velocity information diversity of population numerical experiment

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Vibration suppression of structure with electromagnetic shunt damping absorber

Vibration suppression of structure with electromagnetic shun...

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16th International Symposium on Applied Electromagnetics and Mechanics (ISEM)

作者： Xie, Shilin Li, Peichao Zhang, Xinong Yan, Bo Xi An Jiao Tong Univ Sch Aerosp State Key Lab Strength & Vibrat Mech Struct Xian 710049 Shaanxi Peoples R China

The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization method is presented to determine the main working parameters of EMSDA on the basis of the built theoretical model. The objective function minimizing the response variance of system under white noise excitation is formulated. The particle swarm optimization algorithm is employed in optimization. The simulated and experimental studies on vibration control by use of EMSDA are conducted. The results show that the electromagnetic shunt damping absorber can attenuate significantly the structural vibration.

关键词： Electromagnetic shunt damping absorber vibration control optimization particle swarm optimization algorithm

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PSO PARAMETERS optimization FOR EKF AND AKF FOR IM ROTOR SPEED ESTIMATION 16

PSO PARAMETERS OPTIMIZATION FOR EKF AND AKF FOR IM ROTOR SPE...

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16th International Power Electronics and Motion Control Conference and Exposition (PEMC)

作者： El Merraoui, K. Ferdjouni, A. Univ Saad Dahleb Dept Elect F Technol Blida Algeria

ISBN: (纸本)9781479920600

This paper presents the application of a Metaheuristic optimization algorithm for determining the parameters of a PI controller and the values of the state and measurement noise of Kalman Filter. The particle swarm optimization is a new technique that is used to solve complex problems. It minimizes a cost function under the cooperation of many individuals. Kalman Filter is used here to estimate the stator currents and rotor fluxes of the induction motor. The performances of the extended Kalman Filter and the adaptive Kalman Filter are analyzed. They are applied to estimate stator currents;rotor fluxes and rotor speed of the induction motor, and thus help to overcome the speed sensor, which is expensive and bulky. The extended Kalman Filter requires extending the state vector to rotor speed, which implies to use the linearization of the model. The adaptive Kalman Filter consists of determining the rotor speed adaptation law. The stability of the estimation error is proved using a Lyapunov function.

关键词： particle swarm optimization algorithm Kalman Filter induction motor Lyapunov function adaptation law

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Online optimization for the multi-objective operation of electric multiple units based speed limits curve 11

Online optimization for the multi-objective operation of ele...

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11th World Congress on Intelligent Control and Automation

作者： Yang, Hui Liu, Hong-En Fu, Ya-Ting East China Jiaotong Univ Sch Elect & Elect Engn Nanchang Jiangxi Peoples R China Key Lab Adv Control & Optimizat Jiangxi Prov Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781479958252

The electric multiple units (EMU) provide a transport service in the dynamical running environment, which should meet the requirements of safety, punctuality, precise train stopping, energy conservation and comfort simultaneously. However, since pervious manual operation method of EMU is mainly based on a given V-S curve (velocity versus position curve) and drivers' experience, it cannot meet the multi-objective operation requirements in real time. In order to improve the operation strategy, this paper develops a multiobjective online optimization model for the EMU operation based on speed limit curve. Then, we optimize the operation strategy using a modified multi-objective particle swarm optimization algorithm on line, so as to obtain the Pareto optimal solution set. Further, based on the delay state of EMU running process, we pick out the optimal operation strategy from the Pareto set. Finally, the running process of the EMU operated on the optimal operation strategy can satisfy the multi-objective requirements. And the experimental results on the field data of CRH380AL (China railway high-speed EMU type-380AL) running process show the real time effectiveness of the proposed approach.

关键词： Electric multiple units Speed limit Operation strategy Multi-objective online optimization particle swarm optimization algorithm

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Research on Prediction of Egg Freshness based on Improved GRNN

Research on Prediction of Egg Freshness based on Improved GR...

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International Conference on Mechatronics and Semiconductor Materials (ICMSCM 2013)

作者： Yang, Jian Shi, Ying Li, Xiuying Wang, Xin Yin, Yingying Jilin Agr Univ Informat Technol Teaching & Management Ctr Changchun Peoples R China

ISBN: (纸本)9783037859391

The purpose of this paper is to add particle swarm optimization algorithm to Generalized Regression Neural Network for predicting egg Haugh value and evaluating freshness degree of eggs. Firstly process the egg images with light-transmitting were obtained by the computer vision device including denoising, threshold segmentation, conversing HSI Color model and calculating the averages of hue, saturation, and intensity in the center of the image. Secondly analyze GRNN, and then particle swarm algorithm to optimize according to the predicted formula being derived. Thirdly train Improved GRNN and predicate Haugh value by HSI parameter data as the sample. The value of residual errors of Improved GRNN model are 6.38, the correct discerning rate of grading table eggs is 91.2%. It proves better than traditional BP neural network in terms of predicted accuracy and robustness.

关键词： Freshness degree of eggs Nondestructive detection Generalized Regression Neural Network Machine Vision particle swarm optimization algorithm

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Bandwidth and Power Allocation for Two-Way Relaying in Overlay Cognitive Radio Systems

Bandwidth and Power Allocation for Two-Way Relaying in Overl...

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IEEE Global Communications Conference (GLOBECOM)

作者： Alsharoa, Ahmad Ghazzai, Hakim Yaacoub, Elias Alouini, Mohamed-Slim King Abdullah Univ Sci & Technol KAUST Thuwal Makkah Province Saudi Arabia QMIC Doha Qatar

ISBN: (纸本)9781479935123

In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In our framework, we propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as an amplify-and-forward two-way relays, they are used to support PUs to achieve their target data rates over the remaining bandwidth. More specifically, CUs acts as relays for the PUs and gain some spectrum as long as they respect a specific power budget and primary quality-of-service constraints. In this context, we first derive closed-form expressions for optimal transmit power allocated to PUs and CUs in order to maximize the cognitive objective. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the optimal relay amplification gains and optimal cognitive released bandwidths as well. Our numerical results illustrate the performance of our proposed algorithm for different utility metrics and analyze the impact of some system parameters on the achieved performance.

关键词： Overlay cognitive radio systems two-way relaying technique particle swarm optimization algorithm

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Performance optimization of DOA Estimation in Non-Uniform Linear Antenna Array by PSO algorithm

Performance Optimization of DOA Estimation in Non-Uniform Li...

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2nd International Conference on Mechanical Design and Power Engineering (ICMDPE 2013)

作者： Han, Huilian Wan, Liangtian Si, Weijian Beijing Aerosp Automat Control Inst Natl Key Lab Sci & Technol Aerosp Intelligence Co Beijing Peoples R China Harbin Engn Univ Informat & Commun Engn Coll Harbin Peoples R China

ISBN: (纸本)9783038350019

In order to estimate the coherent source, a modified multiple signal classification (MUSIC) algorithm is introduced. And a novel arrangement method for the non-uniform linear array by particle swarm optimization (PSO) algorithm is proposed. This method needs merely a signal source whose direction-of-arrival (DOA) has been exactly known. The proposed method has a simple processing and a strong stabilization. It could be applied to optimized arbitrary array configuration. The simulation verifies that the performance of DOA estimation is improved effectively, which has proved the validity of the proposed method.

关键词： DOA estimation non-uniform array particle swarm optimization algorithm

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