Description: 基于图的二分算法，使用c++编写，执行效率非常高，特别适用于网络划分-Bipartite graph-based algorithm, the use of c++ Preparation, implementation efficiency is very high, especially for network segmentation Platform: |
Size: 31744 |
Author:大赛分 |
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Description: 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 Platform: |
Size: 7168 |
Author:陈帅军 |
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Description: 各种算法模板（二分图最大匹配匈牙利算法、最小生成树prime和kruskal算法、Dijkstra算法、两点最短路径负权值边SPFA算法、图任意两点最短路径Floy算法、网络最大流SAP算法、网络最大流最小费用算法、乘法逆元gcd扩展求解算法、线段树区间划分统计算法、矩阵n次方分治法求解、gcd算法、整数划分问题、函数最小点问题、十进制转ACM算法、素数筛选法和欧拉函数求解、快模算法、字符串匹配KMP算法、字典全排列算法、快排、三维度排序、）-Various algorithms template (bipartite graph matching Hungarian algorithm, the minimum spanning tree the prime and kruskal algorithm, Dijkstra algorithm, two shortest path negative weight value side SPFA algorithm, Fig any two points on the shortest path Floy algorithms, network flow SAP algorithms, network maximum flow minimum cost algorithm multiplicative inverse gcd expansion algorithm, segment tree interval division statistical algorithms, the matrix of the n-th power of divide and conquer to solve the gcd algorithm, integer division problem, the minimum point of the function, decimal turn ACM algorithm, primes screening method solving and Euler function, fast mode algorithm, the string matching KMP algorithm, a dictionary full array algorithm, fast row, the sort of three dimensional) Platform: |
Size: 18432 |
Author:林云 |
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Description: 利用泊松分布构建的复杂网络的二分网络演化建模-Poisson distribution building complex networks of Bipartite network evolution model Platform: |
Size: 2048 |
Author:haohao |
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Description: use the HeatS+ProbS hybrid algorithm introduced by Zhou et al. [74] on the two bipartite networks to determine the edge weight in both miRNA projections. By which, the resource transfer process, as one of the weighting methods for one-mode projection of a bipartite network [73], was used to weight the miRNA projection of the lncRNA-miRNA and miRNA-EF association bipartite networks. Our algorithm start computing weight matrices and associated with each of the two bipartite networks using the HeatS+ProbS algorithm. These two weight matrices are then used to obtain the combined weight matrix and, therefore, compute the recommendation matrix .-use the HeatS+ProbS hybrid algorithm introduced by Zhou et al. [74] on the two bipartite networks to determine the edge weight in both miRNA projections. By which, the resource transfer process, as one of the weighting methods for one-mode projection of a bipartite network [73], was used to weight the miRNA projection of the lncRNA-miRNA and miRNA-EF association bipartite networks. Our algorithm start computing weight matrices and associated with each of the two bipartite networks using the HeatS+ProbS algorithm. These two weight matrices are then used to obtain the combined weight matrix and, therefore, compute the recommendation matrix . Platform: |
Size: 1024 |
Author:jiezhou |
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Search - bipartite network