资源列表
PSO_ELM
- 运用粒子群算法对ELM算法进行优化，以达到算法的最优性。(Particle swarm optimization (PSO) is applied to optimize the ELM algorithm to achieve the optimality of the algorithm.)
Recognition
- 将数量较少的故障样本分为训练集和测试集，实现故障的分类和识别(A small number of fault samples are divided into training set and test set to realize fault classification and recognition.)
卷积神经网络python代码
- 用于进行图像识别与大型图像的处理，是一种高效的识别方法(It is an efficient recognition method for image recognition and large image processing.)
pytorch-vae-master
- 变分子编码 重构图像 Mnist 特征提取(vae reconstruction Mnist feature extracting)
ACO for TSP
- 蚁群算法解决旅行商问题，能够成功运行并且有结果(Ant colony algorithm can solve the traveling salesman problem and run successfully.)
PSO-BP
- 粒子群算法优化BP神经网络，在传统PSO算法的基础上增加了惯性权重，并且线性递减策略改变。(Particle Swarm Optimization (BP) algorithm optimizes BP neural network, and inertia weights are added based on traditional PSO algorithm, and linear decreasing strategy changes)
adaboost
- 程序为一种分类算法AdaBoost算法，用于解决二分类问题(The program is a classification algorithm AdaBoost algorithm to solve the two classification problem)
kMeans
- kMeans 的 Python代码实现, 还有python自带库的kMeans 的实现(The realization of kMeans's Python code, as well as the realization of kMeans with Python's own library.)
算法
- 编程语言为C++的几个常见算法源码，提供给大家(Programming language for C++ several common algorithm source code, to everyone.)
ASTAR
- 路径规划A*算法的python实现，带有详尽注释(Path planning A* algorithm Python implementation, with detailed notes)
k-means.py
- 通过python实现了k-means分类。(The python implementation of the K-means classification.)
alexnet
- alexnet网络结构，基于python语言下的tensorflow框架(The network structure of alexnet)