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蚁群ACO-PSO

于 2019-06-09 发布

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下载积分: 1 下载次数: 12

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代码说明：

说明：蚁群算法混合粒子群算法的matlab程序(Matlab Program of Ant Colony Algorithm Mixed Particle Colony Algorithm)

文件列表：

ACO-PSO\ant_pso.m, 4222 , 2008-03-23
ACO-PSO\ca_tsp.m, 144 , 2007-11-22
ACO-PSO\cross_tsp_a.m, 477 , 2007-12-05
ACO-PSO\cross_tsp_b.m, 419 , 2007-12-05
ACO-PSO\cross_tsp_c.m, 417 , 2007-12-05
ACO-PSO\cross_tsp_d.m, 438 , 2007-12-05
ACO-PSO\mutation_a.m, 141 , 2007-12-05
ACO-PSO\mutation_b.m, 195 , 2007-12-05
ACO-PSO\mutation_c.m, 208 , 2007-12-05
ACO-PSO\mutation_d.m, 261 , 2007-12-05
ACO-PSO, 0 , 2010-05-28

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2010-10-28 10:23:01下载

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Inverse zig zag scan used after zigzag scan to arrange the data back to 2d matrix or image

2010-05-07 17:50:14下载

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阵列处理程序，40阵元，3信源，实现信号子空间拟合，噪声子空间拟合(Array processing, array element 40, 3 sources, to achieve signal subspace fitting, noise subspace fitting)

2011-05-13 06:13:16下载

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Kalman-filter-algorithm
卡尔曼滤波算法(内含详细推导)，可供读者自行学习，经本人测试，代码无误(Kalman filter algorithm (including the detailed derivation))

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simulink教程,学习如何进行动态仿真(simulink course, learn how to simulate the dynamic)

2011-11-04 10:55:12下载

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exam2_1995
Elnagar, G., et al. (1995). "The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40(10). 上述文章的算例2的仿真代码(Elnagar, G., et al. (1995). " The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40 (10). the simulation code of example 2 in the preceding article.)

2013-10-18 12:54:32下载

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基于KL变换的目标识别技术，个人认为效果比神经网络要好(KL transform based target identification technology, think better results than the neural network)

2013-12-21 16:40:47下载

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WSN DRAWING USING MATLAB SOFTWARE PACKAGE

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ce travail aborde l authentification et édentification en biometrie avec l enpreinte digital

2015-03-07 00:50:19下载

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建立LibSVM预测模型，基于网格算法、粒子群算法、遗传算法优化了模型参数，并由最终模型预测了给定切削参数下零件的粗糙度等级。(Establish LibSVM prediction model, grid-based algorithm, particle swarm optimization, genetic algorithm to optimize the parameters of the model, the final model prediction given by the cutting parameters of parts roughness class.)

2016-11-27 21:14:20下载

积分：1

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