资源列表
Selforg
- 自组织特征映射网络进行图像分类识别（神经网络实用教程）-Self-organizing feature map network image classification Recognition [Neural Network Practical Guide]
FS
- 模糊神经网络预测地基沉降量（神经网络实用教程中源码）-Fuzzy neural network prediction of foundation settlement [neural network practical tutorial source]
ga
- 基于遗传神经网络的图像分割[神经网络实用教程中的实例]-Based on Genetic Neural Network for Image Segmentation [neural network tutorial and practical examples]
rbf11
- 分类是我们经常用到的，本算法用径向基函数实现了分类-Classification, we are frequently used, the algorithm using radial basis function implementation of the classification
lm
- 基于LM神经网络的房地产开发风险预测[神经网络实用教程中的实例]-LM-based neural network prediction of risk in real estate development [neural network tutorials and practical examples]
ch3
- 神经网络实用教程----第三章源码（很不错喔）-Neural Network Practical Guide---- Chapter III source [Oh well]
DPSO
- 综合的微粒群智能分类算法，考虑了不同的学习因子，可根据不同的数据特点进行选择。-Particle Swarm integrated intelligent classification algorithms, taking into account different learning factor, according to the characteristics of different data selection.
gaknn2008-12-08
- 本算法是实现基于KNN的基因遗传算法，是对KNN算法的改进，具有更好的分类效果。-gaKnn[Genetic Algorithm Optimized K Nearest Neighbor Classification framework] is a frameowork for KNN optimization with a genetic algorithm.
generic_tsp
- 用遗传算法求解TSP问题，种子数100，遗传概率和交叉概率可以在源程序中修改。-Genetic Algorithm with TSP problem, a few hundred seeds, genetic probability and crossover probability can modify the source program.
tsp
- hopfield神经网络求解TSP问题，改程序设置了10个城市的随机位置，进而解决城市间最短路径问题。-hopfield neural network to solve TSP problem, the procedures set up to 10 cities random location, then the shortest path between cities to solve problem.
generic2
- 遗传算法求解极值的源程序，只需将要求函数在源文件中输入，即可，种子数100，变异概率和交叉概率可调-Extremes of genetic algorithm source code, simply will be asked to function in the source file type, you can, seed number of 100, mutation probability and crossover probability adjustable
eightcode
- 优化后A*算法解八数码难题，只需要在源文件中将初始化的八数码输入即可，具有很好的泛化性。-Optimized solution of A* algorithm eight digital problems and only required source files will be initialized in the eight digital input, has a good generalization of.