登录
首页 » matlab » Adaptive-CPSO-master

Adaptive-CPSO-master

于 2020-05-11 发布
0 162
下载积分: 1 下载次数: 1

代码说明:

说明:  改进的粒子群优化,有效解决全局最优,实现化工过程的温度优化(Improved particle swarm optimization to effectively solve global optimization)

文件列表:

Adaptive-CPSO-master, 0 , 2016-04-27
Adaptive-CPSO-master\.gitattributes, 378 , 2016-04-27
Adaptive-CPSO-master\.gitignore, 649 , 2016-04-27
Adaptive-CPSO-master\CEC2005, 0 , 2016-04-27
Adaptive-CPSO-master\CEC2005\A1.m, 6794 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ACPSO.m, 6994 , 2016-04-27
Adaptive-CPSO-master\CEC2005\EF8F2_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\E_ScafferF6_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\E_ScafferF6_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\E_ScafferF6_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\E_ScafferF6_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\E_ScafferF6_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\README.txt, 5303 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ackley_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ackley_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ackley_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ackley_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\ackley_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\automataActSel.m, 347 , 2016-04-27
Adaptive-CPSO-master\CEC2005\automataProbUp.m, 636 , 2016-04-27
Adaptive-CPSO-master\CEC2005\b.m, 86 , 2016-04-27
Adaptive-CPSO-master\CEC2005\benchmark_func.m, 27327 , 2016-04-27
Adaptive-CPSO-master\CEC2005\body.m, 1681 , 2016-04-27
Adaptive-CPSO-master\CEC2005\elliptic_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\elliptic_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\elliptic_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\elliptic_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\exemplar.m, 1042 , 2016-04-27
Adaptive-CPSO-master\CEC2005\fbias_data.mat, 248 , 2016-04-27
Adaptive-CPSO-master\CEC2005\func_plot.m, 1716 , 2016-04-27
Adaptive-CPSO-master\CEC2005\global_optima.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\griewank_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\griewank_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\griewank_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\griewank_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\griewank_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\high_cond_elliptic_rot_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func1_M_D10.mat, 8792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func1_M_D2.mat, 7592 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func1_M_D30.mat, 72792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func1_M_D50.mat, 200792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func1_data.mat, 8184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func2_M_D10.mat, 8792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func2_M_D2.mat, 1112 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func2_M_D30.mat, 72792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func2_M_D50.mat, 200792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func2_data.mat, 8184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_HM_D10.mat, 8792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_HM_D2.mat, 1112 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_HM_D30.mat, 72792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_HM_D50.mat, 200792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_M_D10.mat, 8792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_M_D2.mat, 1112 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_M_D30.mat, 72792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_M_D50.mat, 200792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func3_data.mat, 8184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func4_M_D10.mat, 8792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func4_M_D2.mat, 1112 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func4_M_D30.mat, 72792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func4_M_D50.mat, 200792 , 2016-04-27
Adaptive-CPSO-master\CEC2005\hybrid_func4_data.mat, 8184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\pso.m, 3030 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rastrigin_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rastrigin_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rastrigin_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rastrigin_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rastrigin_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\rosenbrock_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\schwefel_102_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\schwefel_206_data.mat, 21040 , 2016-04-27
Adaptive-CPSO-master\CEC2005\schwefel_213_data.mat, 41104 , 2016-04-27
Adaptive-CPSO-master\CEC2005\sphere_func_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\table.asv, 75 , 2016-04-27
Adaptive-CPSO-master\CEC2005\table.m, 111 , 2016-04-27
Adaptive-CPSO-master\CEC2005\test.m, 5168 , 2016-04-27
Adaptive-CPSO-master\CEC2005\test_data.mat, 104928 , 2016-04-27
Adaptive-CPSO-master\CEC2005\weierstrass_M_D10.mat, 984 , 2016-04-27
Adaptive-CPSO-master\CEC2005\weierstrass_M_D2.mat, 216 , 2016-04-27
Adaptive-CPSO-master\CEC2005\weierstrass_M_D30.mat, 7384 , 2016-04-27
Adaptive-CPSO-master\CEC2005\weierstrass_M_D50.mat, 20184 , 2016-04-27
Adaptive-CPSO-master\CEC2005\weierstrass_data.mat, 984 , 2016-04-27
Adaptive-CPSO-master\Readme.md, 1996 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc, 0 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\ACPSO.m, 6432 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\automataActSel.m, 347 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\automataProbUp.m, 596 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\b.m, 86 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\body.m, 1654 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\body1.m, 466 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\body2.m, 469 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\clpso.m, 3411 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\exemplar.m, 1042 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\fit_func.m, 2226 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\icpsoh.m, 8487 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\learn.m, 6505 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\orthm_generator.m, 305 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\rcpsoh.m, 9065 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\splitswarm.m, 1256 , 2016-04-27
Adaptive-CPSO-master\TEC2006_RotatedFunc\test.m, 1046 , 2016-04-27
Adaptive-CPSO-master\TEC2006_StandardFunc, 0 , 2016-04-27

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • Random
    This sample code is to generate random number in C#
    2014-08-11 02:38:37下载
    积分:1
  • boost_peak_current_control
    Boost变换器的电流反馈控制,闭环系统,实用简练,好用。(Boost converter current feedback control, closed-loop system, practical and concise, easy to use.)
    2014-09-23 22:17:46下载
    积分:1
  • forward-algorithm
    这是一个隐马尔可夫模型前向算法,各位亲可以下载使用,一般用于计算分类,预测,等等(This is a hidden Markov model before the algorithm, you can download pro, generally used to calculate the classification, prediction, etc.)
    2014-12-04 15:01:42下载
    积分:1
  • LLE
    Locally linear embedding(LLE)是一个经典的流形学习降维方法,通过LLE发现高维数据潜在的内在维数,可以简化计算、方便可视化处理等。(Locally linear embedding (LLE) is a classic manifold learning dimensionality reduction method, discovered by LLE potential inherent high dimensional data dimension, the calculation can be simplified to facilitate visual processing.)
    2013-11-27 19:28:30下载
    积分:1
  • 灰色预测模型及关联度分析
    计算灰色预测中数据的关联度 以及灰色模型的算法实现(Computing the correlation of data in grey prediction model and the algorithm realization of grey model)
    2018-02-07 00:02:04下载
    积分:1
  • DSPAMb
    利用Matlab/DSP Builder 建立AM信号发生器模型。(Matlab/DSP Builder )
    2010-11-14 09:45:57下载
    积分:1
  • newpoly
    说明:  数值分析的newpoly算法的matlab实现(newpoly the matlab implementation)
    2011-04-02 14:35:55下载
    积分:1
  • a-lot-of-fiber-mode
    一组光纤模型,单模光纤和多模光纤都有,很好用(a lot of fiber mode)
    2012-08-16 18:42:09下载
    积分:1
  • reil
    基于MATLAB的瑞利信道建模程序,可针对MIMO信道进行仿真(MIMO channel simulation based on MATLAB Rayleigh channel modeling program,)
    2013-05-08 20:53:21下载
    积分:1
  • matrices_aleatoires_SemP_LNM_1801
    Matrices aleatoires : Statistique asymptotique des valeurs propres
    2012-01-13 19:00:50下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载