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粒子群优化算法C
- 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-comparison with the genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function op
粒子群算法程序以及优化神经网络程序
- 粒子群算法程序以及优化神经网络程序,测试通过
PSOGABPDRNN.rar
- 此包含有遗传算法、粒子群算法、BP算法优化对角递归神经网络的MATLAB程序,This includes genetic algorithms, particle swarm optimization, BP algorithm for diagonal recurrent neural network of the MATLAB program
psoBP.rar
- 基于粒子群的ＢＰ神经网络算法的ＭＡＴＬＡＢ实现（源程序）,基于粒子群的ＢＰ神经网络算法的ＭＡＴＬＡＢ实现（源程序）
algorithms
- 我个人收集的各类智能算法，共有20多个源代码，包括：遗传算法，蚁群算法，粒子群算法，微分进化算法，遗传神经网络算法，粒子群SVM算法，粒子群神经网络算法等混合算法-I collect all kinds of intelligent algorithms, a total of more than 20 source code, including: genetic algorithms, ant colony optimization, particle swarm optimization,
Matlab
- 各类人工智能算法源代码哦，包括蚁群、粒子群、遗传、神经网络-The source code of various artificial intelligence algorithms Oh
pso-bp
- 这是一个采用粒子群算法优化bp神经网络权值的MATLAB程序-This is a particle swarm optimization using neural network weights bp MATLAB program
pso_wavelet
- 小波神经网络模型，采用粒子群算法优化，包含单输入、多输入-Wavelet neural network model, using particle swarm optimization, including single-input, multiple-input
psoyouhuannyj
- 基于粒子群优化的神经网络训练算法研究论文 摘 要: 本文提出了基于连接结构优化的粒子群优化算法(SPSO) 用于神经网络训练,该算法在训练神经网络权 值的同时优化其连接结构,删除冗余连接,使神经网络获得与模式分类问题匹配的信息处理能力. 经SPSO 训练的神经 网络应用于Iris ,Ionosphere 以及Breast cancer 模式分类问题,能够部分消除冗余分类参数及冗余连接结构对分类性能 的影响. 与BP 算法及遗传算法比较,该算法在提高分类误差精度的同时可加快训
GA_BP-pso_bp
- 遗传算法与神经网络混合的算法程序、粒子群优化与神经网络混合的算法程序，可以进行算法结果的比较-Genetic algorithm and neural network algorithm for mixed procedures, particle swarm optimization and neural network algorithm for mixed procedures, can be the result of comparison algorithm
Optimization_of_RBF_Network
- Matlab粒子群算法优化RBF网络 采用了粒子群算法对RBF神经网络中的参数进行了优化，在测试程序中验证了经过粒子群算法优化的RBF神经网络的函数逼近能力比未经过优化的逼近能力强-Matlab PSO RBF network optimization using particle swarm optimization on RBF neural network parameters are optimized, in the test procedures and verified thr
PSO_GA_RBF
- 粒子群算法、遗传算法优化RBF径向基神经网络。-Particle swarm optimization, genetic algorithm optimization of RBF Radial Basis Function Neural Networks.
psoooLMBP
- 用粒子群算法和LM算法结合的方式训练神经网络，求函数的最小值。-Using Particle Swarm Optimization and the LM algorithm combines the approach for training neural networks, seeking the minimum value of the function.
bp2
- 利用粒子群PSO算法，设计一个使得前向神经网络的训练得到最优问题。-The use of particle swarm PSO algorithm, designed to allow a feed-forward neural network training problems to be optimal.
PSO_BP
- 基于粒子群和BP神经网络的混合优化策略算法。将改进PSO算法与BP神经网络结合，用PSO算法取代梯度下降法来优化神经网络的连接权值和阈值。程序简单易懂。-Based on Particle Swarm and the BP neural network algorithm for hybrid optimization strategy. Will improve the PSO algorithm and BP neural network, using PSO algorithm to re
POS-GA
- 一篇关于粒子群算-遗传算法优化BP神经网络的文章，应用背景股票预测。-Article on the particle swarm optimization- genetic algorithm BP neural network articles, application background stock forecasting.
Parrecasting
- 混沌粒子群算法的神经网络短时交通流预测Particle swarm optimization based on chaotic neural network short-term traffic flow forecasting-Particle swarm optimization based on chaotic neural network short-term traffic flow forecasting
粒子群PID
- 该代码为基于pso算法优化的PID神经网络的系统控制算法(The code is based on the PSO algorithm optimized PID neural network system control algorithm)
粒子群算法优化RBF网络
- 粒子群算法优化RBF网络，有相关解释，matlab源码！可以跑通(Particle swarm optimization RBF network, there are relevant explanations, matlab source code! You can run through.)
遗传粒子群优化算法-GAPSO
- 混沌粒子群优化算法，及其该算法的简单应用(A SIMPLE IMPLEMENTATION OF THE PARTICLE SWARM OPTIMIZATION)