Search - particle swarm optimization

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[Documents] 基于带变异算子的粒子群优化算法 DL : 0: 基于带变异算子的粒子群优化算法下载PDF文件-with variations based on the Operator Particle Swarm Optimization algorithm to download PDF files!
Date : 2025-12-30 Size : 240kb User : 林玲
[Documents] QPSO1 DL : 0: Particle swarm optimization with particles having quantum behavior
Date : 2025-12-30 Size : 288kb User : 叶子
[Documents] pso DL : 0: particle swarm optimization introduction
Date : 2025-12-30 Size : 157kb User : mohammad
[Documents] pso DL : 0: Particle Swarm Optimization
Date : 2025-12-30 Size : 49kb User : sina mehrabi
[Documents] PSO-SVM DL : 0: 改进PSO-SVM在说话人识别中的应用。通过对粒子群优化算法中惯性权重和全局最优值的分析，提出了一种根据迭代次数而自适应变化的惯性权重的粒子群优化方法-Improvement in the PSO-SVM speaker recognition applications. Through particle swarm optimization algorithm in the inertia weight and the analysis of the global optimum value, a number of iterations in accordance with changes in the adaptive inertia weight particle swarm optimization method
Date : 2025-12-30 Size : 308kb User : 彭伟
[Documents] pso1 DL : 0: the source code for particle swarm optimization algorithm is given in this file. the source code is for economic dispatch problem which is a power system problem.
Date : 2025-12-30 Size : 12kb User : sathish
[Documents] 20090316082518135 DL : 0: 采用改进的粒子群算法解决生产优化中的问题 -Particle Swarm Optimization algorithm to solve the production
Date : 2025-12-30 Size : 334kb User : daijiang
[Documents] 1 DL : 0: 粒子群算法的程序代码，简单易用，是采用c语言实现的-Particle swarm optimization code, easy to use, achieved using c language
Date : 2025-12-30 Size : 9kb User : shenqizao
[Documents] OPSO DL : 0: Research on multi-mode resource constrained project scheduling based on particle swarm optimization algorithm.rar
Date : 2025-12-30 Size : 3.96mb User : 张人龙
[Documents] PSO_matlab DL : 0: 粒子群算法 Matlab编程实现这个程序就是最基本的粒子群优化算法程序，用Matlab实现，非常简单。只有几十行代码。-Particle swarm algorithm Matlab programming, this program is the basic particle swarm optimization algorithm procedures, using Matlab, very simple. Only a few dozen lines of code.
Date : 2025-12-30 Size : 9kb User : neo
[Documents] dace2 DL : 1: 粒子群优化的kriging近似建模程序包DACE-PSO，matlab程序，比传统的dace程序包优势是：不用确定Sigma参数-Kriging particle swarm optimization modeling package DACE-PSO, matlab program, compared with the traditional dace package advantage is: do not determine the Sigma parameters
Date : 2025-12-30 Size : 3.27mb User : 方涛涛
[Documents] Editorial-for-the-special-issue-on-Particle-Swarm DL : 0: Editorial for the special issue on Particle Swarm Optimization
Date : 2025-12-30 Size : 85kb User : ouissam
[Documents] An-integrated-multidisciplinary-particle-swarm.ra DL : 0: An integrated multidisciplinary particle swarm optimization approach to conceptual ship design
Date : 2025-12-30 Size : 357kb User : ouissam
[Documents] A-SHOT-BOUNDARY-DETECTION-ALGORITHM-BASED-ON DL : 0: Shot boundary detection is always an important topic in digital video processing. It is the first important task of content-based video retrieval and indexing. In this paper, a new shot boundary detection algorithm is proposed, based on Particle Swarm Optimization Classifier. This method firstly takes the difference curves of U-component histograms as the characteristics of the differences between video frames, and then utilizes a Slide-Window Mean Filter to filter difference curves and a KNN Classifier applying PSO to detect and classify the shot transitions. This method has three advantages that it is more sensitive to gradual transitions each curve graphic with remarkable characteristics corresponds to a shot transition Cuts and Gradual transitions could be detected in a same step. As experiments shown, the performance of this method is superior to the traditional shot boundary detection methods, and this method can achieve high recall and precision rate.-Shot boundary detection is always an important topic in digital video processing. It is the first important task of content-based video retrieval and indexing. In this paper, a new shot boundary detection algorithm is proposed, based on Particle Swarm Optimization Classifier. This method firstly takes the difference curves of U-component histograms as the characteristics of the differences between video frames, and then utilizes a Slide-Window Mean Filter to filter difference curves and a KNN Classifier applying PSO to detect and classify the shot transitions. This method has three advantages that it is more sensitive to gradual transitions each curve graphic with remarkable characteristics corresponds to a shot transition Cuts and Gradual transitions could be detected in a same step. As experiments shown, the performance of this method is superior to the traditional shot boundary detection methods, and this method can achieve high recall and precision rate.
Date : 2025-12-30 Size : 386kb User : saeed
[Documents] ciis DL : 0: Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives
Date : 2025-12-30 Size : 1.02mb User : f&f
[Documents] IC DL : 0: Particle Swarm Optimization (PSO) Based Turbine Control
Date : 2025-12-30 Size : 647kb User : f&f
[Documents] 06925921 DL : 0: Comparison of Distributed and Centralized control for Partial Shading in PV Parallel Based on Particle Swarm Optimization Algorithm
Date : 2025-12-30 Size : 989kb User : omar
[Documents] 93-103-1-PB DL : 0: Tuning of PID Controller Using Particle Swarm Optimization (PSO) Tuning of PID Controller Using Particle Swarm Optimization (PSO)
Date : 2025-12-30 Size : 431kb User : zaghba
[Documents] Genetic Algorithm DL : 0: 1-BINARY GENETIC ALGORITHM 2-CONVERTS BINARY CHROMOSOME TO CONTINUOUS VARIABLES 3-CONTINUOUS GENETIC ALGORITHM 4-PARETO GENETIC ALGORITHM 5-PERMUTATION GENETIC ALGORITHM 6-TRAVELING SALESPERSON PROBLEM COST FUNCTION 7-PARTICLE SWARM OPTIMIZATION 8-ANT COLONY OPTIMIZATION 9-TEST FUNCTIONS
Date : 2017-05-03 Size : 62.43kb User : signuptest1396
[Documents] 配电网络重构matlab代码 DL : 2: 基于粒子群算法的配电网重构matlab程序(Matlab program of distribution network reconfiguration based on particle swarm optimization)
Date : 2025-12-30 Size : 152kb User : Yuki小盆与

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