资源列表
PSO_base_RBF
- PSO+RBF神经网络预测，较为先进的搜索方式- PSO+ RBF neural network prediction
Desktop
- Numerical analysis: Newton method used to solve the nonlinear problems.
ford-max-flow
- 解决最小费用最大流问题，一般有两条途径。一条途径是先用最大流算法算出最大流，然后根据边费用，检查是否有可能在流量平衡的前提下通过调整边流量，使总费用得以减少？只要有这个可能，就进行这样的调整。调整后，得到一个新的最大流。-Minimum cost maximum flow problem to solve, there are generally two ways. One way is to use a maximum flow algorithm to calculate the maxim
best-fit
- 匹配算法是通过给每个顶点一个标号（叫做顶标）来把求最大权匹配的问题转化为求完备匹配的问题的。-Matching algorithm is through a label for each vertex (called the top mark) to seek the power matching problem into a complete matching problem.
Minimum-Cost-Flow
- 最小费用最大流问题是经济学和管理学中的一类典型问题。在一个网络中每段路径都有“容量”和“费用”两个限制的条件下，此类问题的研究试图寻找出：流量从A到B，如何选择路径、分配经过路径的流量，可以达到所用的费用最小的要求。-Minimum cost maximum flow problem is economics and management in a class of typical problems. Each path in a network has the " capacity&q
minimum-spanning-tree
- 在一个具有几个顶点的连通图G中，如果存在子图G 包含G中所有顶点和一部分边，且不形成回路，则称G 为图G的生成树，代价最小生成树则称为最小生成树。 -Has several vertices in a connected graph G, if there subgraph G ' contains all vertices of G and part of the side, and does not form a loop, called G' is a spanning tr
Coloring-Problem
- 图着色问题（Graph Coloring Problem, GCP）又称着色问题，是最著名的NP-完全问题之一。路线着色问题是图论中最著名的猜想之一。-Graph coloring problem (Graph Coloring Problem, GCP), also known as coloring problem, is the most famous NP-complete problems. Line graph coloring problem is one of the most
traversing-binary-tree
- 用于构建二叉树，并且有条件地遍历二叉树结构类型的数据，是一种常见的数据结构-it can be used to creat the binary tree,and traverse the binary tree,it s a common used data struct
programmpowerflow
- Complex Power Flow, param,pfs_gsm, symetrical component with graph ,Symmetrical Fault Analysis ,Ybus and Zbus
PageRank
- 自己实现的pagerank算法，比较经典的一个的、算法，有兴趣的可以看看。-Realize their own pagerank algorithm, more classic one, algorithms, are interested can look at.
matlab
- 主要适用于matlab图形处理中的各种边界提取-Mainly applied in a variety of graphics processing matlab boundary extraction
PID
- 有位置型PID改编的增量型PID算法，适合初学者学习-With incremental PID algorithm position PID adaptation, suitable for beginners to learn