搜索资源列表
GA
- 程序1：遗传算法和非线性规划函数的优化； 程序2：基于遗传算法的BP神经网络优化； 程序3：基于遗传算法的TSP算法； 程序4：基于遗传算法的LQR控制器优化设计 程序5：基于遗传算法的函数优化-Program 1: genetic algorithms and nonlinear programming function optimization Program 2: Based on the genetic algorithm BP neural network optim
BPPID_matlab
- 一种BP神经网络整定的PID算法，含注释-BP neural network tuning PID algorithm, including the Notes
ICA-wind-prediction
- 采用最先进的殖民竞争算法Imperialist competition algorithm优化BP神经网络的初始权值、阈值，进行风电功率预测，带数据和实例，ica为主程序-Using the most advanced colonial competitive algorithm Imperialist competition algorithm to optimize the initial weights of BP neural network, threshold, carry wind
ga-wind-prediction
- 运用GA遗传算法优化BP网络，对风电功率进行预测，含实际数据和案例。-GA genetic algorithm to optimize the use of BP network prediction for wind power, with actual data and case studies.
chapter3
- 基于遗传算法的BP神经网络优化算法Matlab实现-Optimization algorithm based on genetic algorithm BP neural network
eee
- 遗传算法优化bp神经网络，采用的是实数编码方式。-Genetic algorithm optimization bp neural network, using real number encoding.
decoder_BP_SE_ref
- 置信传播即BP译码算法，在每一次迭代过程中,都要对全部比特和校验信息进行更新,存在计算量大、译码效率低的问题,故提出了单边传播信息的迭代BP算法-Belief Propagation that BP decoding algorithm, in each iteration, we must check for all the bits and update the information, there is a large amount of calculation, low coding e
decoder_BPML
- 置信传播(belief propagation,BP)算法的计算复杂度较高，且变量节点和校验节点间信息传递的信息可靠，但是迭代的实现，就最大似然算法来说，验证其提高译码性能的特点。 -Belief propagation (belief propagation, BP) higher computational complexity of the algorithm, and reliable information between variable nodes and check node
beiyesizhengzehua
- 采用贝叶斯正则化算法提高 BP 网络的推广能力,采用两种训练方法-Bayesian regularization algorithm to improve the generalization ability of BP network, using two training methods
dastebandi
- Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni
estekhraj-vijegi
- Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni
GP-optimization
- 整个算法分成三部分，第一个部分是神经网络整体结构的确定，然后是遗传算法对参数的优化，然后便是利用已经优化好的参数，利用神经网络进行预测。我们根据需要优化的权值以及阈值的数量确定算法个体的长度。个体通过适应度函数计算他们的适应度，根据适应度的大小，我们使用轮盘算法，确定他们的遗传，交叉还有变异等过程，优化以后的BP神经网络可以更好地收敛。-The whole algorithm is divided into three parts, the first part is to determine
PSO-optimization
- 应用粒子群算法来寻找BP神经网络最优的初始权值还有阈值，本程序主要是以此来拟合函数，读者可以根据需要，小小地修改一下BP神经网络的代码，可以实现诸如模式识别等功能，收敛效果很好，-Application of particle swarm algorithm to find the optimal initial BP neural network weights as well as the threshold value, the procedure is a way to fit func
GA_BP
- 遗传算法对BP神经网络的优化，帮助其优化参数，在进行训练-Genetic algorithm (ga) optimization of BP neural network, help the optimization parameters, in the training
NeuralNetwork_BP_Classification
- 用matlab实现了人工神经网络的Bp网络算法，有利于图形图像的提取和识别-Using matlab realize the artificial neural network Bp network algorithm, is conducive to extraction and recognition of graphic images
EEG_BP2
- 使用BP神经网络算法对脑电信号进行分类识别。-BP neural network algorithm using EEG classification.
application
- matlab 遗传算法优化BP神经网络完成代码 调试通过-matlab genetic algorithm to optimize BP neural network to complete the code debugging through
BP1111
- bp神经网络的数据分类-语音特征信号分类 bp神经网络的非线性系统建模-非线性函数的拟合-Linear systems neural network modeling of nonlinear systems, according to the classification of BP neural network genetic algorithm to optimize BP neural network
BPpp
- 遗传算法优化 B P 神经网络非线性函数拟合 根据遗传算法和 B P 神经网络理论-Genetic algorithm optimization BP neural network - non-linear function fitting B P based on genetic algorithms and neural network theory
chap10
- 关于用遗传算法改进BP神经网络的matlab实现(转引) ga优化神经网权值&阈值程序。 优化的基本原理和过程很多论文可以查到，在此不必赘述我就把用gaot5的小程序贴在下面吧，也是y=1/x(为看的方便，比较繁杂的也有) -About matlab improved BP neural network using genetic algorithm implementation (quoted) ga optimizing neural network weights & T