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

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Fault Localization of Distribution Network Based on Reverse-Local Learning based particle swarm optimization algorithm 3

Fault Localization of Distribution Network Based on Reverse-...

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3rd International Conference on Energy and Electrical Power Systems (ICEEPS)

作者： Zhang, Wei Zhou, Yangjun Yi, Chenying Li, Shan Feng, Bin Huang, Weixiang Pan, Juntao Zhou, Yuanchao Wu, Lifang Guangxi Power Grid Co Ltd Elect Power Res Inst Guangxi Key Lab Intelligent Control & Maintenance Nanning Peoples R China Guangxi Power Grid Co Ltd Nanning Peoples R China Guangxi Power Grid Co Ltd Nanning Power Supply Bur Nanning Peoples R China

ISBN: (纸本)9798350375145;9798350375138

With the large-scale access of distributed generation, the power flow characteristics of distribution network have been greatly changed. The conventional fault localization methods for distribution networks are no longer applicable. To deal with the problems induced by large-scale access of distributed generation, a novel fault localization method based on improved particle swarm optimization algorithm is proposed in this paper. Aiming at the issues of potential misjudge, an objective function/ fitness value correction method is proposed to adapt to bidirectional power flow induced by distributed generation. Aiming at the issues of sluggish convergence and poor robustness in existing models, this paper introduces the Reverse-Local Learning based particle swarm optimization algorithm to improve the optimization efficiency and algorithm stability. Case study is performed on the IEEE-33 bus distribution network to demonstrate the accuracy and efficiency of the proposed fault localization method.

关键词： fault localization distributed generation bidirectional power flow particle swarm optimization algorithm

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An Improved particle swarm optimization algorithm

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International Conference on Mechanical Engineering and Intelligent Systems (ICMEIS 2012)

作者： Jiang, Changyuan Zhao, Shuguang Guo, Lizheng Ji, Chuan Donghua Univ Coll Informat Sci & Technol Shanghai 201600 Peoples R China

ISBN: (纸本)9783037854693

Based on the analyzing inertia weight of the standard particle swarm optimization (PSO) algorithm, an improved PSO algorithm is presented. Convergence condition of PSO is obtained through solving and analyzing the differential equation. By the experiments of four Benchmark function, the results show the performance of S-PSO improved more clearly than the standard PSO and random inertia weight PSO. Theoretical analysis and simulation experiments show that the S-PSO is efficient and feasible.

关键词： particle swarm optimization algorithm inertia weight sinusoidal changing differential equation

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Research on Electronic Materials with Design of a down-conversion mixer Based on particle swarm optimization algorithm

Research on Electronic Materials with Design of a down-conve...

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2nd International Conference on Function Materials and Nanotechnology (FMN 2013)

作者： Shan, Huilin Zhang, Yinsheng Nanjing Univ Informat Sci & Technol Nanjing 210044 Jiangsu Peoples R China

ISBN: (纸本)9783037858059

This paper presents principles of a down-converted mixer for four sub-harmonic and proposes a particle swarm optimization algorithm as a global search algorithm, and the performance equation is used as the assessment of the mixer circuit optimization method. Dielectric substrate adopts Electronic Materials with RF/Duroid 5880 whose dielectric constant is 2.20 and 5mil in thickness. The optimization algorithm can quickly get optimal results. The simulation results show that this mixer achieves higher 1 dB compression point, loss of frequency conversion which is less than 15 dB and good linearity.

关键词： particle swarm optimization algorithm Sub-harmonic mixer down-converted mixer

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A Modified particle swarm optimization algorithm for Dynamic Multiresponse optimization Based on Goal Programming Approach 21

A Modified Particle Swarm Optimization Algorithm for Dynamic...

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21st International Conference on Management Science & Engineering (ICMSE)

作者： Zhang Liu-yang Ma Yi-zhong Zhu Lian-yan Wang Jian-jun Nanjing Univ Sci & Technol Sch Econ & Management Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9781479953769

While many of the previous applications based on the Taguchi method only focus on single-response optimization in static system, dynamic multiresponse optimization has received only limited attentions. optimization of dynamic multiresponse aims at finding out a setting combination of input controllable factors that will result in optimal solutions for all response variables at each signal level. However, it is often difficult to find an optimal setting when multiple responses are simultaneously considered because of their contradiction among the requirements. Hence, a new robust design optimization procedure based on response surface methodology is proposed in the article. The polynomial models of system sensitivity and the error variance for each response are firstly fitted, and corresponding individual desirability functions based on their respective characteristic are defined. Then, goal programming approach is used to resolve multiresponse optimization problems. Because the problems are often multiobjective optimization problems and are often with multipeak distribution, multiconstraint and high nonlinearity, traditional gradient algorithms are easy to obtain local optimal solutions. So a modified particle swarm optimization algorithm is proposed to search global optimal solution. The example shows that the proposed approach can obtain more effectively solutions for dynamic multiresponse optimization problems.

关键词： dynamic multiresponse multiobjective optimization goal programming response surface methodology particle swarm optimization algorithm

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An application of particle swarm optimization algorithm to permutation flowshop scheduling problems to minimize makespan, total flowtime and completion time variance

An application of Particle Swarm Optimization Algorithm to p...

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IEEE International Conference on Automation Science and Engineering

作者： Chandrasekaran, S. Ponnambalam, S. G. Suresh, R. K. Vijayakumar, N. Monash Univ Sch Engn Malaysia Campus Jaya 46150 Selangor Malaysia SRK Vidhyala Acetech Comp Educ Coimbatore 641020 Tamil Nadu India Sri Ramakrishna Mission Vidyalaya Polytech Coll Dept Engn Mech Coimbatore Tamil Nadu India Amrita Sch Engn Dept Mech Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781424403103

The problem of scheduling in flowshops with the objective of minimizing makespan, total flowtime and completion time variation is studied in this paper. A simple discrete version of particle swarm optimization algorithm (PSO) is proposed for solving the set of benchmark flowshop scheduling problems proposed by Taillard [1]. The obtained results are better when compared with the results published in the literature.

关键词： flowshop scheduling particle swarm optimization algorithm makespan total flowtime and completion time variance

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Fault Diagnosis Analysis with Support Vector Regression and particle swarm optimization algorithm

Fault Diagnosis Analysis with Support Vector Regression and ...

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22nd Chinese Control and Decision Conference

作者： Tian, WenJie Liu, JiCheng Beijing Union Univ Beijing Automat Inst Beijing 100101 Peoples R China

ISBN: (纸本)9781424451821

The fault diagnosis model with support vector regression (SVR) and particle swarm optimization algorithm (POSA) for is proposed. The novel structure model has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. The impact factor of fault behaviors is discussed. With the ability of strong self-learning and faster convergence, this fault detection method can detect various fault behaviors rapidly and effectively. by learning the typical fault characteristic information. Utilizing the character that principal components analysis algorithm can keep the discern ability of original dataset after reduction, the reduces of the original dataset are calculated and used to train individual SVR for ensemble, and consequently, increase the detection accuracy. To validate the effectiveness of the proposed method, simulation experiments are performed based on the electronic circuit dataset. The results show that the proposed method is a promised method owning to its high diversity, high detection accuracy and faster speed in fault diagnosis.

关键词： Support Vector Regression Principal Components Analysis Fault Diagnosis Reduction particle swarm optimization algorithm

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optimization of PID Controller for Underwater Autonomous Vehicle Based on particle swarm optimization algorithm 3

Optimization of PID Controller for Underwater Autonomous Veh...

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3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Li, Hongna Fan, Yiqun Tianjin University of Technology Maritime College Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350382426

In order to ensure that the underwater autonomous vehicle can maintain the stability of control performance when performing unknown tasks, this paper combines the particle swarm optimization algorithm with PID controller, and compares the particle swarm optimization PID simulation with fuzzy PID simulation and traditional PID simulation, and concludes that the use of particle swarm optimization algorithm to optimize the PID parameters has a certain feasibility, which improves the stability and control performance of the system. © 2023 IEEE.

关键词： particle swarm optimization algorithm PID controller underwater autonomous vehicle

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Using particle swarm optimization algorithm in Multimedia CDN Content Placement

Using Particle Swarm Optimization Algorithm in Multimedia CD...

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5th International Symposium on Parallel Architectures, algorithms and Programming (PAAP)

作者： Chen, Jian-Bo Chen, Chu-Chuan Ming Chuan Univ Dept Informat & Telecommun Engn Tao Yuan Taiwan

ISBN: (纸本)9780769548982;9781467345668

Multimedia Content Delivery Networks (CDN) is used to improve the performance and reliability on Internet. In CDN architecture, the multimedia contents are replicated from the origin server to replica servers in order to improve the performance and minimize the use of network bandwidth. Efficient placing the multimedia contents in CDN is a challenging problem. There are five factors that can be used to determine the placement of multimedia contents, they are bandwidth availability, connection availability, storage availability, CPU availability, and memory availability. In this paper, a particle swarm optimization (PSO) algorithm is adopted to solve this issue. PSO algorithm uses these five different input parameters as different dimensions. In this five dimension searching space, PSO algorithm can find out the global optimal solution. With this global optimal solution, it is the most appropriate replica server that must place the multimedia content. The simulation results show that the PSO algorithm can achieve a better performance than other algorithms.

关键词： component CDN Content Placement particle swarm optimization algorithm

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Adaptive particle swarm optimization algorithm Based on Levy Flights Mechanism

Adaptive Particle Swarm Optimization Algorithm Based on Levy...

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Chinese Automation Congress (CAC)

作者： Du, Zhongzhou Li, Si Sun, Yi Li, Nana Zhengzhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou Henan Peoples R China

ISBN: (纸本)9781538635247

This article aims to the problems that the particle swarm optimization (PSO) algorithm has slow convergence and easy to fall into local optimum, provides an improved adaptive particle swarm optimization algorithm based on Levy flight mechanism (LFAPSO). The long jumps of Levy flight will step out of the local optimum in the local search. The convergence speed and accuracy of the LFAPSO algorithm are certified on 6 typical test functions. The simulation results show that the LFAPSO algorithm is obviously more successful than chaotic particle swarm optimization algorithm with adaptive mutation (ACPSO) and adaptive particle swarm optimization (APSO) algorithm in convergence performance and robustness. Furthermore, the results demonstrate the LFAPSO algorithm works better to solve the multidimensional function. The method will be used to different optimization problems such as scheduling problems, training neural networks, image segmentation, etc.

关键词： adaptive particle swarm optimization algorithm levy flight

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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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