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graph
- 图论的算法，最短路，最小生成树，连通，匹配，网络流及应用。-Graph theory, algorithms, shortest path, minimum spanning tree, connectivity, matching, network flow and applications.
lujin
- 最短路径问题（用无向图表示n个城市之间的交通网络建设规划，顶点表示城市，边上的权表示该线路的造价，试设计一个方案，使得这个交通网的总造价最小。）-The shortest path problem (with undirected graph n cities that transport links between the construction plan, vertex, said city, said the right edge of the construction cost of
RoutingSystem
- The task in this assignment is to implement an airline routing system. Your system should be able to read in a ight network as a graph from a le, where airports are represented as vertices and ights between airports are represented as ed
Graph_Theory
- 图论模型及方法 搞计算机算法和数学建模的人都知道图论是一个很重要的内容。本资料介绍了图论中的最短路算法、匹配、邮递员和货郎问题、最小生成树、网络流等经典问题。而且有非常经典易懂的Matlab程序。-Graph theory and methodology of engaging in computer algorithms and mathematical modeling of the people know that graph theory is a very important cont
toci
- Complex networks have some common basic model, such as random graph, WS small-world networks, NW small-world networks and scale-free BA network, the program generated from the mechanism of these networks to generate the complex network model and anal
Graph
- 1．建立无向网的邻接矩阵。 要求：从键盘输入无向网的顶点数和边数；然后以“顶点1，顶点2，权值”的方式输入图的各边，建立邻接矩阵存储，并输出各顶点和邻接矩阵。 2．对无向网进行深度优先遍历，输出遍历序列。 3.判断给定的无向网是否是连通的？ 要求：从键盘上输入出发点进行搜索遍历，输出遍历序列。 -1. The establishment of the network adjacency matrix. Requirements: No input from the ke
Algorithms.In.C.3rd.Ed.Part5.Graph.Algorithms
- 经典算法书(中文版)。这一套算法系列书介绍了当今最重要的算法，共分3卷，这是第2卷（第五部分），集中讲解图算法。本书共有6章（第17章～第22章）。第17章详细讨论图性质和类型，第18章~第22章分别讲解图搜索、有向图和DAG、最小生成树、最短路径以及网络流。书中提供了用C语言描述的完整算法源程序，并且配有丰富的插图和练习。-Algorithms in C, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewi
graph
- 实现各种图的网络结构的实现方法，是学习传感器网络的很好的软件-Network structure to achieve a variety of graph realization method is good to learn a software sensor networks
Basedonthecognitivenetworkofgraphcoloringmodelofth
- 本文研究了认知网络中基于图论着色模型的频谱分配算法。-This paper studies the cognitive network model based on graph theory spectrum allocation algorithm for coloring.
matlabyiqunsuanfa
- 蚁群算法是一种用来在图中寻找优化路径的机率型算法。是一种求解组合最优化问题的新型通用启发式方法，该方法具有正反馈、分布式计算和富于建设性的贪婪启发式搜索的特点。通过建立适当的数学模型，基于故障过电流的配电网故障定位变为一种非线性全局寻优问题。-Ant colony algorithm is a method used to find optimal path in the graph the probability-based algorithm. Is a combination of opt
@graph
- 复杂网络分析工具包，计算Clustering Coefficient，Assortativity和全局最短路径等参数-Complex network analysis tools package, calculated Clustering Coefficient, Assortativity and global parameters such as shortest path
Complete-collection-of-algorithm
- 算法大全 全书分30章及2附录（在MATLAB中实现）对常用数学算法进行汇总介绍。 主要包括：线性规划、非线性规划、动态规划、图与网络、排队论、对策论、层次分析法、插值与拟合、数据的统计描述和分析、方差分析、回归分析、微分方程建模、稳定状态模型、常微分方程解法、差分方程模型、马氏链模型、变分法模型、神经网络模型、偏微分方程的数值解、目标规划、模糊数值模型、现代优化算法、时间序列模型、存贮论、经济与金融的优化问题、生产与服务运作管理中的优化问题、灰色系统理论及其应用、多元分析、偏最小二乘回归以
Bipartite-graph-matching-template
- 求二分图匹配多种算法，网络流最大流的部分模板-Find a variety of bipartite graph matching algorithms, network flow part of the template maximum flow
CSGC
- 认知无线电网络频谱分配的颜色敏感的图着色算法,是个很经典的算法-Cognitive radio network' s spectrum allocation of color-sensitive graph coloring algorithm, the algorithm is a very classic
Graph-characteristics
- 基于34人的Karate俱乐部网络，找出基本的网络特性-Based on the 34-vertex Karate Club network model, calculate the related graph characteristics: degree, betweenness centrality, closeness centrality, eigenvector(pagerank) centrality, clustering coefficients
Dijkstra
- 在C环境中使用Dijkstra算法解决网络图中两点间最短路径。-Between two points in the network graph shortest path.
Graph
- 关于复杂网络社团结构的相关程序，其中包括求节点间最短距离，求边介数等等。-There are some procedures about community structure of comlex network which includes the shortest distance between nodes and betweeness and so on.
ConvertToXML
- 将得到的Matlab中的数据转换为vizster可用的XML格式。其中，vizster是网络领域一个很好的布局程序-Convert Matlab data to vizster data format。vizster is a good network graph visual tools
Diagrams--network--and-Algorithms
- 关于图论的一些基本算法，有兴趣的可去看下，会有收获的-On some of the basic algorithm of graph theory, interested to see, there will be harvested
Graph-based clustering and data visualization algorithms
- This Matlab package is written specifically for the book Ágnes Vathy–Fogarassy and János Abonyi: Graph-based clustering and data visualization algorithms. The purpose of the package is to demonstrate a wide range of graph-based clustering and visuali