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

共 1411 条记录，以下是151-160 订阅

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Grey Model Based particle swarm optimization algorithm For Fatigue Strength Prognosis of Concrete

Grey Model Based Particle Swarm Optimization Algorithm For F...

引用

International Conference on Advances in Materials and Manufacturing Processes

作者： Liu, Qinming Dong, Ming Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Anatai Coll Econom & Management Shanghai 200052 Peoples R China

ISBN: (纸本)9780878492015

This paper explores the grey model based PSO (particle swarm optimization) algorithm for fatigue strength prognosis of concrete. First, depending on concrete's testing status, fatigue life is studied. Then, one GM(1,1) based PSO algorithm is used in fatigue strength prognosis of concrete. One important advantage of the proposed algorithm is that only fewer data is in need for fatigue strength prognosis. Finally, a case study is given to illustrate effectiveness and efficiency of the proposed approach.

关键词： Fatigue strength Grey model particle swarm optimization algorithm Building materials

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Hybrid particle swarm optimization algorithm for Solving Systems of Nonlinear Equations

Hybrid Particle Swarm Optimization Algorithm for Solving Sys...

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IEEE International Conference on Granular Computing

作者： Ouyang, Aijia Zhou, Yongquan Luo, Qifang Guangxi Univ Nationalities Coll Math & Comp Sci Nanning 53006 Peoples R China

ISBN: (纸本)9781424448319

A hybrid particle swarm optimization (HPSO) algorithm, which combines the advantages of Nelder-Mead simplex method (SM) and particle swarm optimization (PSO) algorithm, is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for SM and inaccuracy of PSO due to being easily trapped into local optimal. The algorithm has sufficiently displayed the performance of PSO's global searching and SM's accurate local search. Numerical computation results show that the approach has great robust, high convergence rate and precision, it can give satisfactory solutions of nonlinear equations.

关键词： systems of nonlinear equations simplex method particle swarm optimization algorithm

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Vertical particle swarm optimization algorithm and its application in soft-sensor modeling

Vertical particle swarm optimization algorithm and its appli...

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6th International Conference on Machine Learning and Cybernetics

作者： Yang, Wei-Ping Shanghai DianJi Univ Sch Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781424409723

Vertical particle swarm optimization algorithm (VPSO) is proposed in this paper. The new algorithm assumes that the particles tend to fly towards two directions. One is flying toward the global best particle. The other is flying toward the vertical direction. And there is a random value produced in every iteration step to measure the probability of flying into two directions. Both VPSO and particle swarm optimization algorithm (PSO) are used to train neural network (NN) and applied in soft-sensor of acrylonitrile yield. Finally, simulation results show that the method proposed by this paper is feasible and effective in soft-sensor of acrylonitrile yield.

关键词： particle swarm optimization algorithm optimization acrylonitrile soft-sensing

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An Acoustic Echo Cancellation Scheme Based on particle swarm optimization algorithm

An Acoustic Echo Cancellation Scheme Based on Particle Swarm...

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IEEE Region 10 Conference on TENCON 2010

作者： Mahbub, Upal Acharjee, Partha Pratim Fattah, Shaikh Anowarul Bangladesh Univ Engn & Technol Dept Elect & Elect Engn Dhaka 1000 Bangladesh

ISBN: (纸本)9781424468904

This paper deals with the problem of echo cancellation of speech signals in an acoustic environment. In this regard, generally, different adaptive filter algorithms are employed, which may lack the flexibility of controlling the convergence rate, number of iterations, range of variation of filter coefficients, and tolerance consistency. In order to overcome these problems, unlike conventional approaches, we formulate the task of echo cancelation as a coefficient optimization problem whereby we introduce the particle swarm optimization (PSO) algorithm. In this case, the PSO is designed to perform the error minimization in frequency domain. From extensive experimentations, it is shown that the proposed PSO based acoustic echo cancellation method provides high echo cancellation performance in terms of echo return loss enhancement with a faster convergence rate in comparison to that obtained by some of the state-of-the-art methods.

关键词： Echo cancellation adaptive filter particle swarm optimization algorithm speech analysis frequency domain optimization

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Multi-objective Optimal Sizing Hybrid Power System in a Solar Electric Vehicle Using particle swarm optimization algorithm

Multi-objective Optimal Sizing Hybrid Power System in a Sola...

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4th International Conference on Manufacturing Science and Engineering (ICMSE 2013)

作者： Zhou Shiqiong Guo Guifang Xiang Yongyang Shenzhen Inst Informat Technol Dept Traff & Environm Shenzhen Peoples R China Tibet Univ Int Informat Engn Dept Tibet Peoples R China

ISBN: (纸本)9783037856932

In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.

关键词： Multi-objective optimal sizing Hybrid power particle swarm optimization algorithm Solar electric vehicle (SEV)

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Discrete particle swarm optimization algorithm for Lot-streaming No-wait Flow Shop Scheduling Problem

Discrete Particle Swarm Optimization Algorithm for Lot-strea...

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2nd International Conference on Advanced Engineering Materials and Technology (AEMT)

作者： Yang, Lin Pan, Yuxia Hainan Univ Sanya Coll Sanya 572022 Hainan Peoples R China

ISBN: (纸本)9783037854471

This paper proposed discrete particle swarm optimization(DPSO) algorithm to solve lot-streaming no-wait flow shop scheduling problem(LNFSP) with the objective of the maximum completion time. The natural encoding scheme based on job permutation and newly-designed methods were adopted to produce new individuals. After the DPSO-based exploration, a efficient fast local search based on swap neighborhood structure is used to enhance the exploitation capability. Simulation results show the effectiveness of the proposed algorithms.

关键词： particle swarm optimization algorithm lot-streaming no-wait flow shop scheduling problem local search

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Performance Evaluation of particle swarm optimization algorithm for Optimal Design of Belt Pulley System

Performance Evaluation of Particle Swarm Optimization Algori...

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4th International Conference on swarm, Evolutionary, and Memetic Computing (SEMCCO)

作者： Sabarinath, Pandurengan Thansekhar, M. R. Saravanan, R. KLN Coll Engn Pottapalayam 630611 India JCT Coll Engn & Technol Coimbatore Tamil Nadu India

ISBN: (纸本)9783319037530;9783319037523

The present scenario in the design of machine elements includes the minimization of weight of the individual components in order to reduce the overall weight of the machine elements. It saves both cost and energy involved. Belts are used to transmit power from one shaft to another by means of pulleys which rotate at the same speed or different speeds. Generally, the weight of pulley acts on the shaft and bearings. In the present study, minimization of weight of a belt pulley system has been investigated. particle swarm optimization algorithm (PSO) is used to solve the above mentioned problem subjected to a set of practical constraints and it is compared with the results obtained by Differential Evolution algorithm (DEA). Our results indicate that PSO approach handles our problem efficiently in terms of precision and convergence and it outperforms the results presented in the literature.

关键词： Optimal Design Belt pulley system particle swarm optimization algorithm

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Study on Passenger Train Stopping Scheme Based on Improved particle swarm optimization algorithm

Study on Passenger Train Stopping Scheme Based on Improved P...

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IEEE International Conference on Intelligent Computing and Intelligent Systems

作者： Wang, Shuang Zhao, Peng Qiao, Ke Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China

ISBN: (纸本)9781424447541

This paper develops a multi-objective optimization model for the passenger train stopping scheme on high-speed railway lines Minimizing the stopping times for all passenger trains, minimizing travel distance of empty trains and minimizing the number of transfer passengers are the three planning objectives of the model For a given travel demand and specified capacity of stops, the model is solved by heuristic algorithm An improved discrete particle swarm optimization (PSO) algorithm is presented to determine the best-compromise train stopping scheme with high effectiveness and stability In the algorithm, a stop based representation is designed, and a new method is used to update the position and velocity of particles In order to keep the particle swarm algorithm from premature stagnation, the simulated annealing algorithm, which has local search ability, is combined with the PSO algorithm to make elaborate search near the optimal solution, then the quality of solutions is improved effectively An empirical study on a given small railway network is conducted to demonstrate the effectiveness of the model and the performance of the algorithm The experimental results show that the hybrid algorithm has great advantages in both success rate and convergence speed compared with other discrete PSO algorithm and genetic algorithm, and an optimal set of stopping schemes can always be generated for a given demand To achieve the best planning outcome, the stopping schemes should be flexibly planned, and not constrained by specific ones as often set by the planner

关键词： high-speed railway lines passenger train stopping scheme multi-objective programming particle swarm optimization algorithm simulated annealing algorithm

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Localization Technology Based on Quantum-behaved particle swarm optimization algorithm for Wireless Sensor Network

Localization Technology Based on Quantum-behaved Particle Sw...

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

作者： Zhao, Ji Fu, Yi Wang, Han-bo Wuxi City Coll Vocat Technol Dept Elect Informat Engn Wuxi 214000 Jiangsu Peoples R China

ISBN: (纸本)9783037855034

This paper proposed a distributed iterative localization technology of wireless sensor networks (WSNs) to solve the problem of node localization. In this approch, once the nodes get localized, they act as references for the rest of nodes to localize. The ranging-based localization problem is formulated as a multidimensional optimization issue, and the quantum-behaved particle swarm optimization algorithm (QPSO) is used to exploit their quick convergence to quality solutions. Finally, the simulation results compared with the particle swarm optimization algorithm (PSO) algorithm show that QPSO outperforms the PSO and improve the node position accuracy, which prove the validity of the presented method.

关键词： quantum-behaved particle swarm optimization algorithm particle swarm optimization algorithm location wireless sensor networks

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A Reactive Power optimization Method for AC Metro Power Supply System Based on particle swarm optimization algorithm 19

A Reactive Power Optimization Method for AC Metro Power Supp...

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20th IEEE Vehicle Power and Propulsion Conference (IEEE VPPC)

作者： Feng, Ding Zhou, Haiqi Lin, Sheng Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

ISBN: (纸本)9798350344455

Aiming at the problem of reactive power imbalance in AC metro, the equivalent circuit model is established by investigating the topology AC metro power supply system, and the change of reactive power in the whole day of the system is analyzed in combination with the actual operation data of the metro. The reactive power evaluation indices are proposed to evaluate the influence of reactive power on the system. To solve the problem that the power factor of the system at night does not meet the requirements and there is no available device in the line for reactive power optimization, the particle swarm optimization (PSO) is used to obtain the optimal configuration of reactive power compensation devices. The results show that the balance and optimization of reactive power can be achieved through reasonable configuration of compensation devices.

关键词： AC metro power supply system reactive power optimization particle swarm optimization algorithm

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