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检索条件"主题词=PSO algorithm"

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Sonar Image Registration Based on Improved pso and Powell Hybrid algorithm

Sonar Image Registration Based on Improved PSO and Powell Hy...

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2nd International Conference on Mechatronics and Intelligent Materials (MIM 2012)

作者： Wang, Da Bian, Hongyu Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

ISBN: (纸本)9783037853849

In order to further improve the accuracy of the sonar image registration, a novel hybrid algorithm was proposed. It proposed the normalized mutual information as similar estimation, drawn on multi-resolution data structure based on wavelet transform, a low precision solution was solved by improved pso algorithm, which has strong global search capability, firstly and then a high precision solution was acquired by Powell method, which has strong local search capability. The hybrid algorithm is effective to overcome the fall of local maximum mutual information function;it also improves solution's precision. Since the hybrid algorithm is the initial point of pre-treatment, an effective solution to the Powell method dependence on the initial point. Experiments reveal that the hybrid algorithm is efficiency and effectiveness.

关键词： Image Registration pso algorithm Powell algorithm Mutual Information Sonar Images

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MAXIMUM LOSS REDUCTION AND VOLTAGE PROFILE IMPROVEMENT WITH PLACEMENT OF HYBRID SOLAR-WIND SYSTEM

MAXIMUM LOSS REDUCTION AND VOLTAGE PROFILE IMPROVEMENT WITH ...

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International Conference on Energy Efficient Technologies for Sustainability (ICEETS)

作者： Rekha, E. Sattianadan, D. Sudhakaran, M. SRM Univ Dept EEE Madras Tamil Nadu India Pondicherry Engn Coll Dept EEE Pondicherry India

ISBN: (纸本)9783037857823

Distributed generators(DG) are much beneficial in reducing the losses effectively compared to other methods of loss reduction. It is expected to become more important in future generation. This paper deals with the multi DG's placement in radial distribution system to reduce the system power loss and improve the voltage profile by using the optimization technique of particle swarm optimization(pso). The pso provides a population-based search procedure in which individuals called particles change their positions with time. Initially, the algorithm randomly generates the particle positions representing the size and location of DG. The proposed pso algorithm is used to determine optimal sizes and locations of multi-DGs. The objective function is the combination of real, reactive power loss and voltage profile with consideration of weights and impact indices with and without DG. Test results indicate that pso method can obtain better results on loss reduction and voltage profile improvement than the simple heuristic search method on the IEEE33-bus and IEEE 90-bus radial distribution systems.

关键词： Distributed generation Radial Distribution System Loss Reduction pso algorithm Hybrid solar-wind System

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A Contract-based Model for Dynamic Spectrum Sharing

A Contract-based Model for Dynamic Spectrum Sharing

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8th International ICST Conference on Communications and Networking in China (CHINACOM)

作者： Li, Fangwei Lv, Jing Zhu, Jiang Chongqing Univ Posts & Telecommun Chongqing Key Lab Mobile Commun Technol Chongqing Peoples R China

ISBN: (纸本)9781479914067

Cognitive radio can improve the utilization of spectrum resources through allowing the unlicensed users (i.e., secondary users) use the spectrum of licensed users (i.e., primary users). The spectrum allocation of the primary user is one of the key issues of cognitive radio technology, and that is how to share the spectrum resources with the secondary users. Market-driven spectrum trading is an efficient way for dynamic spectrum sharing. In this paper, we consider the problem of spectrum sharing in the scenario consisting of one primary user and multiple secondary users, and propose a dynamic spectrum sharing model based on contracts and then solve the model by particle swarm optimization (pso) algorithm. In this model, secondary users pay to the primary user according to the obtained actual capacity by a certain percentage. The primary user provides different quality of the channel resources to different secondary users, and the spectrum resources are optimized utilization. Simulation analysis shows that the system efficiency on the model is close to the optimal system efficiency in theory.

关键词： cognitive radio dynamic spectrum sharing contract different quality pso algorithm

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Research on Traffic Signal Cycle Optimization Method Based on Bi-Level Programming Model 3

Research on Traffic Signal Cycle Optimization Method Based o...

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3rd International Conference on Computer Science and Network Technology (ICCSNT)

作者： Yang Zhao-sheng Tian Chun-lin Zhou Xi-yang Yu Yao Jilin Univ Sch Traff Sate Key Lab Automobile Simulat & Control Changchun 130022 Peoples R China

ISBN: (纸本)9781479905614

Aiming at the deficiencies of the traffic signal cycle optimization in the regional traffic signal control system and considering vehicle emission pollution, this paper proposed a traffic signal cycle optimization method based on bi-level programming model, and attempted to take reducing vehicle emission as one of the signal control objective parameters. Then the improved pso algorithm was proposed to solve the optimization model. Finally, the effectiveness of the optimization model and the algorithm was verified through VISSIM and MATLAB. The results indicate that the traffic signal cycle optimization method proposed in this paper can effectively reduce the network delay and vehicle emission

关键词： signal cycle optimization bi-level programming model pso algorithm vehicle emission

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AN OPTIMAL SOUND DETECTION FOR ROBOTS IN AN UNKNOWN ENVIRONMENT

AN OPTIMAL SOUND DETECTION FOR ROBOTS IN AN UNKNOWN ENVIRONM...

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1st International Conference on Communication and Computer Vision (ICCCV)

作者： Saha, Ishani Senthil, A. Mody Inst Technol & Sci Fac Engn & Technol Comp Sci & Engn Dept Lakshmangarh Rajasthan India

ISBN: (纸本)9781479962532

Robot technology has been rapidly developed more & more robots such as humanoid robots work with humans. The objective of this project is to develop a system for an autonomous mobile robot for searching and tracking sound source based target using sound sensors. Finding objects or events by following a sound source direction is an intuitive response for human and animal when they cannot see the target. Lego nxt sound sensor can detect the frequency of sound but is unable to detect the direction from where the sound is originating. pso algorithm has been implemented for the optimization of the exact sound source. pso (particle swarm optimization) is a stochastic population based computational method that optimizes the problem in each iteration, trying to improve the particle solutions and to get better quality of the particles each time. Objective function has been applied to detect the frequency and then the source continuously updates its position on the basis of frequency being detected. So that maximum frequency sound can be detected in minimum possible time and in exact location. Simulation work has been carried out by implementing the pso algorithm in MATLAB to see how exactly the sound sources are detecting the frequency and at what particular frequency the source is exactly detecting the sound. Results have been computed by changing the number of iterations to see the exact location where the sound source is finding the frequency. Thus the main objective of this paper is to compute that the source is detecting the optimized maximum frequency sound by updating its gbest values continuously in every iteration and finally reaching the best possible value.

关键词： pso algorithm Lego NXT sound sensors mobile robot

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Comparison of Cat Swarm Optimization with Particle Swarm Optimization for IIR System Identification

Comparison of Cat Swarm Optimization with Particle Swarm Opt...

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47th Asilomar Conference on Signals, Systems, and Computers

作者： So, J. Jenkins, W. K. Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)9781479923908

Infinite impulse response (IIR) adaptive filters have been developed to identify IIIR systems, but system identification is challenging due to non-unimodality of the error surface and the non-linear relationship between the error signal and the system parameters. Cat Swarm Optimization (CSO) was recently introduced to solve optimization problems with a new learning rule to achieve better performance than particle swarm optimization (pso). Also, it has been used for IIR system identification. This paper examines the parameters of CSO to optimize them for IIR system identification with a few benchmarked IIR plants. Results demonstrate better performance for the CSO algorithm when compared to the inertia-weighted pso algorithm.

关键词： IIR system identification pso algorithm CSO algorithm

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MISSILE GUIDANCE algorithm DESIGN USING PARTICLE SWARM OPTIMIZATION

MISSILE GUIDANCE ALGORITHM DESIGN USING PARTICLE SWARM OPTIM...

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2nd International Conference on Engineering and Technology Innovation (ICETI)

作者： Kung, Chien-Chun Chen, Kuei-Yi Natl Def Univ Chung Cheng Inst Technol Dept Mechatron Energy & Aerosp Engn Tao Yuan Taoyuan County Taiwan Natl Def Univ Chung Cheng Inst Technol Sch Def Sci Tao Yuan Taoyuan County Taiwan

ISBN: (纸本)9783037856123

This paper presents a pso guidance (psoG) algorithm design for the pursuit-evasion optimization problem. The initialized particles are randomly et within the guidance command solution space and the relative distance is taken as the objective function. As the psoG algorithm proceeds, the iteration will execute until the global optimum is reached. Two pursuit-evasion scenarios show that the psoG algorithm has satisfied performance in execution time, terminal miss distance, time of interception, final stage turning rate and robust pursuit capability.

关键词： missile guidance law pso algorithm pursuit-evasion

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the Method of Optimal Phasor Measurement Unit Placement

the Method of Optimal Phasor Measurement Unit Placement

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International Forum on Materials Science and Industrial Technology (IFMSIT 2013)

作者： Zhang Wen-jun Xu Jian-jun Xing Long Northeast Petr Univ Elect & Informat Engn Coll Daqing 163318 Peoples R China Northeast Forestry Univ Coll Mech & Elect Engn Haerbin 150040 Peoples R China

ISBN: (纸本)9783037858417

Taking the full network observability of power system and the least number of PMU as objective, to appearing fault situation in the grid, this paper proposes Differential Evolution and Particle Swarm Optimization (DEpso) algorithm in view of the system failure rate. The improved DEpso algorithm is global optimization, the algorithm takes the constraint condition of fault rate into account during the course of seeking optimal solutions. At the end, through the examples show that the algorithm compares with the existing optimization methods, which can reduce the number of PMU configuration and achieve completely observability of the system, at the same time, and stable operation of the system, through the simulation results verify feasibility and valibity of the algorithm.

关键词： Phasor Measurement Unit DE algorithm pso algorithm optimal placement

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Improving Particle Swarm Optimization algorithm for Distributed Sensing and Search

Improving Particle Swarm Optimization Algorithm for Distribu...

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8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Cai, Yi Chen, Zhutian Min, Huaqing S China Univ Technol Sch Software Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780769550947

Distributed coordination is critical for a multi-robot system in collective cleanup task under a dynamic environment. In traditional methods, robots easily drop into premature convergence. In this paper, we propose a swarm-intelligence based algorithm to reduce the expectation time for searching targets and removing. We modify the traditional pso algorithm with a random factor to tackle premature convergence problem, and it can achieve a significant improvement in multi-robot system. It performs well even in a obstacle environment. The proposed method has been implemented on self-developed simulator for searching task. The simulation results demonstrate the feasibility, robustness, and scalability of our proposed method than previous methods.

关键词： pso algorithm Swarm robotics Collective cleanup Swarm intelligence

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An Improved Expert Intelligent PID Control in Maglev Transportation System with Different Track Irregularities

An Improved Expert Intelligent PID Control in Maglev Transpo...

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2nd International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2013)

作者： Song Rongrong Ma Weihua Chen Zili Southwest Jiaotong Univ Coll Maths Chengdu 610031 Sichuan Peoples R China Southwest Univ Natl Coll Comp Sci & Technol Chengdu Peoples R China

ISBN: (纸本)9783037858585

Track irregularity is one of the most important aspects of the suspension control performance impact in Magnetic Transportation System(MTS). By using the traditional PID control, the problem was that it was difficult to confirm the PID parameters and have long settling time, even appear the chaotic phenomenon. However, using Expert PID(EPID) control method producesd over-fitting to initial assignments, local optimum induced easily and slow convergence rate problem. Based on the global optimization feature of pso algorithm, it had been adopted to optimize the initial values of Expert PID control. An intelligent control algorithm for the maglev transportation system was put forward based on Expert PID optimized by Particle Swarm Optimization algorithm(EPID-pso). The expert rule was that if the absolute value of the error trended to decrease, the PID current control keeped its maintenance;if not, then the PID current control applied strong functions. Under this rule, the dynamic error was reduced and the performance of track irregularity was improved. Simulation results by MATLAB proves that the control scheme has good robustness, shorter adjustment time, faster response time, achieving better quality of control under the three conditions of step signal, low frequence sine wave signal and high frequence square wave signal.

关键词： maglev transportation system track irregularity Expert PID control pso algorithm MATLAB simulation

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