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[Documents] PSO_base_RBF DL : 0: PSO的RBFNN优化程序算法步骤 1.样本数据归一化处理，即将输入输出归一化到[-1,1]区间； 2.确定RBF网络的中心和宽度； 3.以拟合误差的均方根作为性能指标，使用PSO算法优化RBF网络输出层到隐层的连接权值矩阵-PSO-RBFNN algorithm optimization procedures Step 1. Sample data normalization treatment, about input and output normalized to [-1,1] interval 2. To determine the center and width of the RBF network 3. To the fitting error of the mean square roots as a performance index, using the PSO algorithm to optimize RBF network output layer to hidden layer connection weight matrices
Date : 2025-07-03 Size : 4kb User : aKON
[matlab] PSO_base_RBF DL : 0: PSO+RBF神经网络预测，较为先进的搜索方式- PSO+ RBF neural network prediction
Date : 2025-07-03 Size : 4kb User : 杨润华
[Other] PSO_base_RBF DL : 0: 用粒子群算法来优化RBF。此种方法是把粒子群的全局寻优很好的利用到RBF的优化中。-Particle swarm algorithm to optimize RBF. This method is the global particle swarm optimization to good use to optimize the RBF.
Date : 2025-07-03 Size : 4kb User : 李颖
[Other] PSO_base_RBF DL : 0: 基于pso智能算法改进的rbf算法，可以对故障种类进行区分。-Pso intelligent algorithm based on improved rbf algorithm can distinguish the type of fault.
Date : 2025-07-03 Size : 7kb User : 迟警