▍1. 船舶在波浪中的仿真matlab
说明： 波浪模拟，线性波、随机波、船舶受波浪力模拟。(Wave simulation includes linear wave, random wave and wave force on ship.)
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▍2. BP-GA
一种实现话务预测预测算法，基于遗传算法优化神经网络，源码+数据，效果很好(A traffic forecast prediction algorithm based on genetic algorithm optimization neural network source+ data, the effect is very good)
▍3. 遗传算法优化bp神经网络
说明： 遗传算法优化bp神经网络（阀值权值，网络训练，网络预测）(Optimization of BP neural network by genetic algorithm)
▍4. matlab
pn结模拟：一维PN结的模拟 ，有限元法 结合耦合法，新手求交流(Pn junction simulation: one-dimensional pn junction simulation, finite element method combined with coupling method, novice for communication)
▍5. CS-BP
压缩感知重构经典算法-BP算法，试用效果不错相对于OMP好很多，但重构时间较长(compressed sensing；BP algorithm；compressive sensing)
▍8. Kmeans
说明： 给出的程序可用于未知工况的识别或分类问题，属于数据处理的一个环节(The program can be used to identify or classify unknown working conditions, which is a part of data processing)
▍9. rbf
说明： 基于径向基神经网络的仓储机器人路径规划训练代码(Automated Guided Vehicle Path-panning Based on Radial Basis Function Neural Network)
▍10. PSOELM
说明： 极限学习机，粒子群算法，适用于matlab(Extreme learning machine,Particle swarm optimization algorithm)
▍11. Demo_6_VisualizeFeaturesCNN
说明： matlab神经网络工具箱-特征可视化demo(Matlab deep learning toolbox, and show how to visualizing feature)
▍12. 深度学习MATLAB的工具箱 DeepLearnToolbox-master
深度学习MATLAB的工具箱，包括CNN、RNN、CAE、LSTM等复杂的神经网络的代码。(Deep learning MATLAB toolbox, including CNN, RNN, CAE, LSTM and other complex neural network code.)
▍13. 9-3
说明： 负荷预测对电力系统控制、运行和计划都有着重要意义。(Load forecasting plays an important role in power system control, operation and planning.)
▍14. IEEE33base
matlab程序，标准IEEE33节点系统潮流计算程序。(Matlab program, standard IEEE33 node system power flow calculation program.)
▍15. 遗传算法优化RBF
可以实现以下功能：遗传算法优化RBF，GA-RBF(it is used to achieve the goal of GA-RBF)
▍16. spider
机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。(The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model selection, statistical tests and visual plots. Core library objects wilcoxon Wilcoxon object- significance test of results joint_kernel Joint kernel object- for calculating inner products in joint feature spaces joint_data Joint_data object corrt_test corrected resampled t-test object- significance test of results Unsupervised objects spectral Spectral clustering ppca Probabilistic Principal Components Analysis nmf Non-negative Matrix Factorization object mrank Manifold Ranking Density Estimation objects indep Feature selection by independent density estimation Feature Selection objects r2w2_sel Feature scaling/selection via SVMs and r^2/w^2 bound. nfe Non-Linear Feature Elimination mutin)
▍17. 基于两层的层叠自编码的深度学习模型stacked-autoencoder
基于两层的层叠自编码的深度学习模型，前两层用于特征提取，再加一个Softmax分类器用于分类(Two stacked the depth of learning coding model based on the first two levels for feature extraction, coupled with a classifier for classifying Softmax)
▍18. ABC_SVM
svm算法，用于数据挖掘，分类。图像处理(SVM algorithm for data mining, classification. image processing)
▍19. ABC_SVM
蜂群算法优化SVM参数，得到更好的优化效果，算法做了优化(ABC algorithm is employed to optimize SVM to get better result)
▍20. Neural-network-
神经网络的前馈控制仿真，模型是空间漂浮基机器人手臂的动力学方程(The neural network feedforward control simulation model, the model is floating space, the dynamic equations of a robotic arm)
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