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检索条件"主题词=particle Swarm Optimization algorithm"

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Application of particle swarm optimization algorithm to image texture classification

Application of particle swarm optimization algorithm to imag...

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Conference on Medical Imaging, Parallel Processing of Images, and optimization Techniques

作者： Ye, Zhiwei Zheng, Zhaobao Zhang, Jinping Yu, Xin Hubei Univ Technol Sch Comp Sci Wuhan 430068 Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469533

This paper describes a kind of robust texture feature invariant to rotation and scale changes, which is the texture energy associated with a mask generated by particle swarm optimization algorithms. The detail procedure and algorithm to generate the mask is discussed in the paper. Furthermore, feature extraction experiments on aerial images are done. Experimental results indicate that the robust feature is effective and PSO-based algorithm is a viable approach for the "tuned" mask training problem.

关键词： particle swarm optimization algorithm feature extraction tuned mask

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optimization of PMSM Sensorless Control Based on Improved PSO algorithm

Optimization of PMSM Sensorless Control Based on Improved PS...

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International Conference on Manufacturing Science and Technology (ICMST 2011)

作者： Qian Miao-wang Tan Guo-jun Li Ning-Ning Zhao Zhong-xiang China Univ Min & Technol Sch Informat & Elect Engn Xuzhou Jiangsu Peoples R China Xuzhou Heavy Machinery Co Ltd Xuzhou Jiangsu Peoples R China

ISBN: (纸本)9783037852958

For the problem that manual adjustment of the parameters of controller in sensorless control system costs too much time, manpower and always can not get a good result, a new method based on improved particle swarm optimization algorithm is proposed to optimize the parameters. The improved algorithm is based on the standard particle swarm optimization with the simulated annealing algorithm and chaotic search brought in. The speed of motor is estimated by the extend Kalman filter. The error between measured speed and estimated speed of the permanent magnet synchronous motor rotor is used as the fitness function in order that the parameters in the covariance matrix is *** result of simulation indicates that high estimation precision can be got and the motor represents steadily with few of ripple of the actual *** this method, the time of adjustment is reduced and manpower is saved. In addition, the validity of the method is proved in experiment with dSPACE.

关键词： Permanent magnet synchronous motor sensorless control extend Kalman filter particle swarm optimization algorithm dSPACE

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An Intelligent Scheduling Strategy of Collaborative Logistics for Mass Customization

An Intelligent Scheduling Strategy of Collaborative Logistic...

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International Workshop on Information and Electronics Engineering (IWIEE) / International Conference on Information, Computing and Telecommunications (ICICT)

作者： Zhang, Min-Hui Gao, Xiao-Ling Zhou, Xin-Yi JianYang Sichuan Coll Educ Sch Comp Sci Chengdu 611130 Peoples R China

To improve the scheduling optimization of mass customization collaborative logistics, a scheduling solution developed based on the novel particle swarm optimization algorithm was proposed. A mathematic model based on scheduling strategy of mass customization logistics was designed. The novel dynamic particle swarm optimization algorithm framework was given. And simulation experiments were done to validate algorithm. Experiment results show that the proposed algorithm effectively improves the scheduling optimization of mass customization collaborative logistics, which has direct applications for Logistics scheduling (C) 2011 Published by Elsevier Ltd.

关键词： particle swarm optimization algorithm Mass customization collaborative logistics Logistic scheduling

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Two-Stage Multi-Objective Unit Commitment optimization under Future Load Uncertainty

Two-Stage Multi-Objective Unit Commitment Optimization under...

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6th International Conference on Genetic and Evolutionary Computing (ICGEC)

作者： Wang, Bo Li, You Watada, Junzo Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9780769547633;9781467321389

The unit commitment problem is to reduce the total generation cost as much as possible while satisfying future power demands. Therefore, optimization must be performed based on correct predictions of future demands. However, various uncertain factors affect these loads making an exact forecasting unsuccessful. This study mitigates this difficulty by applying fuzzy set theory and the objective is to build a two-stage multi-objective fuzzy programming model. To define the supply reliability effectively, we propose a new concept of maximal blackout time based on the fuzzy credibility theory. In addition, an improved two-layer multi-objective particle swarm optimization algorithm is designed as the solution. Finally, the performance of this study is discussed in comparison with experimental results from several test systems.

关键词： Load uncertainty Fuzzy set theory Two-stage multi-objective Maximal blackout time particle swarm optimization algorithm

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Intelligent optimization of hybrid wind/PV/pumped-storage power system

Intelligent optimization of hybrid wind/PV/pumped-storage po...

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1st International Conference on Energy and Environmental Protection (ICEEP 2012)

作者： Ren, Yan Zheng, Yuan Li, Chong Zhou, Bing Mao, Zhihao Hohai Univ Coll Energy & Elect Engn Nanjing 210098 Jiangsu Peoples R China N China Univ Water Conservancy & Elect Power Inst Elect Power Zhengzhou 450011 Peoples R China Nanjing Inst Technol Nanjing 211167 Peoples R China Patent Examinat Cooperat Ctr Sipo Beijing 1000910 Peoples R China Goupitan power plant Goupitan 564408 Guizhou Peoples R China

ISBN: (纸本)9783037854143

The hybrid wind/PV/pumped-storage power system was the hybrid system which combined hybrid wind/PV system and pumped-storage power station. System optimization was very important in the system design process. particle swarm optimization algorithm was a stochastic global optimization algorithm with good convergence and high accuracy, so it was used to optimize the hybrid system in this paper. First, the system reliability model was established. Second, the particle swarm optimization algorithm was used to optimize the system model in Nanjing. Finally, The results were analyzed and discussed. The optimization results showed that the optimal design method of wind/PV/pumped-storage system based on particle swarm optimization could take into account both the local optimization and the global optimization, which has good convergence high precision. The optimal system was that LPSP (loss of power supply probability) was zero.

关键词： hybrid wind/PV/pumped-storage power system particle swarm optimization algorithm intelligent optimization loss of power supply probability

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Optimal Relay Placement in Microgrids Considering Critical Clearing Time

Optimal Relay Placement in Microgrids Considering Critical C...

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IEEE International Power Engineering and optimization Conference

作者： S. J. Mirazimi B. Salehi M. Tadayon H. R. Karshenas Faculty of Engineering and Surveying University of Southern Queensland (USQ) Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Distribution Network Department Behrad Consulting Engineers Isfahan

ISBN: (纸本)9781467350723

This paper is concerned with the optimal placement of protection devices in a microgrid using particle swarm optimization algorithm. One of the main advantages of Distributed Generation (DG) scheme and microgrids in modern distribution systems is the reduction of number of outages and the associated damages caused by them. This task is accomplished by supplying a feeder from multiple sources. In order to prevent generator instability in DGs connected to utility, it is necessary to improve the protective schemes of traditional distribution systems and also to use proper relaying and setting for DGs. All of the downstream overcurrent (OC) relays of each DG are coordinated together and also should be coordinated with OC relay that is installed on the Point of Common Coupling (PCC) which is set at Critical Clearing Time (CCT) as a definite time, to have a desirable performance on each outage. In this paper, by the use of graph theory, various branches of a feeder are identified and the constraints for using particle swarm optimization algorithm to optimize the location of protective equipment are derived. In the proposed algorithm, the location, type and direction of relays are optimized simultaneously.

关键词： Microgrid particle swarm optimization algorithm Protection-Coordination Graph theory

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Parameter Identification Model with the Control Term in Batch Anaerobic Fermentation

Parameter Identification Model with the Control Term in Batc...

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

作者： Li, Xiaohong Zhang, Shuxi Xu, Zhilong Feng, Enmin Liaoning Univ Sci & Technol Coll Sci Anshan 114051 Liaoning Peoples R China Dalian Univ Technol Sch Environm & Biol Sci & Technol Dalian 116024 Peoples R China Dalian Univ Technol Math Acad Sci Dalian 116024 Peoples R China

ISBN: (纸本)9783037855027

In this paper, according to the characteristics, dynamical behavior and the experimental data of the batch anaerobic culture, a parameter identification model was improved to describe the dynamical system for microorganism in batch fermentation. And some relative characters were introduced. Finally, a PSO algorithm with the inertia weight was used to get the best optimal parameter of the identification model. The results show that the model reduces the errors between the experimental data and computational values, and they can simulate the process of batch fermentation better.

关键词： batch fermentation parameter identification particle swarm optimization algorithm knetics system

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A Hybrid Evolutionary-based Process Mining Technology to Discover Parallelism Structures

A Hybrid Evolutionary-based Process Mining Technology to Dis...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Cheng, H. J. Ou-Yang, C. Juan, Y. C. Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan Ming Chi Univ Technol Dept Ind Engn & Management New Taipei Taiwan

ISBN: (纸本)9781467329453

Information systems have been widely used to support workflow processes to record the execution of tasks in the process and are stored in so-called "event logs". Techniques that relate to events extraction have gotten increasing attention such as process mining techniques. Developed process mining methods such as alpha algorithm, alpha(++) algorithm, and genetic process mining (GPM) are capable of tackling several structures well, but they are still difficult to discover parallelism structures efficiently since the parallelism structures are too complex. This work presents an evolutionary-based process mining approach based on a hybrid of GPM and particle swarm optimization algorithm (PSO) in order to handle parallelism structures. The medical records of acute stroke patients of Taiwanese medical institution are used as a practical case to test the proposed approach. Experimental results on the case show the effectiveness of the proposed approach for tackling parallelism structures.

关键词： Genetic algorithm particle swarm optimization algorithm process mining workflow model

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Research on Intelligence optimization of Web Service Composition for QoS

Research on Intelligence Optimization of Web Service Composi...

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3rd International Conference on Information Computing and Applications (ICICA 2012)

作者： Li, Jianjun Yu, Bin Chen, Wuping Zhengzhou Informat Sci & Technol Inst Zhengzhou 450004 Peoples R China

ISBN: (纸本)9783642340406

With quality of service as the restraint, in accordance with the features of service composition, this paper proposes an intelligent optimization algorithm for Web service composition. By combining a wide search range of shuffled frog leaping algorithm and high accuracy of particle swarm optimization algorithm, this algorithm can find the best one from a lot of service composition schemes. Simulation results show that the algorithm designed by this paper can overcome the low accuracy of shuffled frog leaping algorithm and instability of particle swarm optimization algorithm, and can find the better service composition scheme in all cases.

关键词： Web Service Composition Shuffled Frog Leaping algorithm particle swarm optimization algorithm Intelligent optimization algorithm Quality of Service

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Regional Traffic Control System Study Based on Pattern Identification

Regional Traffic Control System Study Based on Pattern Ident...

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2nd International Conference on Frontiers of Manufacturing and Design Science (ICFMD 2011)

作者： Xia, Baizhan He, Huaiwen Univ Elect Sci & Technol China Zhongshan Inst Zhongshan 528402 Peoples R China

ISBN: (纸本)9783037852828

The thesis introduces traffic patterns definition and identification. Combined with actual project it has established the regional traffic signal coordination and control system based on particle swarm K-means clustering algorithm pattern identification. It puts forward system structure and working principles with discussions focused on several key problems existing in traffic pattern identification process.

关键词： intelligent traffic pattern identification clustering analysis particle swarm optimization algorithm

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