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利用遗传算法对BP神经网络进行能优化并将其用于在特征提取中的应用-BP neural network using genetic algorithm to optimize and be used for applications in feature extraction
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针对传统的ＢＰ或ＧＡ对模糊神经网络的识别应用存在收敛容易陷入局部极小 识别率低下等问题 提出一
种基于ＢＦＧＳ的混合遗传算法 其基本思想为 首先构造一种前馈型模糊神经网络结构 然后用遗传算法进化若干代
后 当目标函数的梯度或者范数小于预先设定值 则改用ＢＦＧＳ算法进行优化识别 仿真实验表明 对比ＧＡ该算法
收敛速度较快 识别精度提高了约７％ 能够较好地应用于一类模糊神经网络的识别-In traditional BP or GA to identify the application
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该程序是遗传算法优化BP神经网络函数极值寻优-The program is a genetic algorithm to optimize BP neural network function optimization extreme
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在matlab软件中编程实现基于遗传算法优化BP神经网络非线性系统拟合算法-In the matlab software programming based on genetic algorithm to optimize the BP neural network nonlinear system fitting method
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Introducing the rank-weight method into the
basic ant colony optimization (ACO), we use the modified
ACO to optimize the weights and thresholds value of neural
networks (NN). And when the BPNN is being trained, this
method can solve the disad
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In this paper three different methods such as GDM
AGDM and modified PSO are adopted to optimize the neural
networks, and simulate the DTC system with
MATLAB/SIMULINK. The result shows: modified PSO
algorithm can solve the problem of neural n
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Wolves optimize neural network to increase the accuracy of pigs, and optimize the weights and thresholds of BP neural network.
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退火算法优化BP神经网络的研究，介绍了一种新的方法(Annealing algorithm to optimize BP neural network)
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