图论导引(Introduction to Graph Theory----Gary Chartrand 图论算法经典书籍 介绍图论基本理论和经典算法实现,例如dijstra算法、最小生成树算法等
2021-09-12 21:52:30 26.75MB 图论算法
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以前下载到一些源代码 但是多少都存在问题 这部分源代码是我修正过的 不知道是否全对 但是书上的例子是验证通过的 另外书籍也在里面 非常方便使用
2021-09-10 15:37:53 24.11MB 图论算法 源代码 matlab
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《图论算法及其MATLAB实现》是2010年北京航空航天大学出版社出版的图书
2021-09-09 12:35:03 24.07MB 图论算法 MATLAB
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5-图论算法1(50页).pdf
2021-09-07 14:08:11 1.71MB 图论算法
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图论PPT,相信对于初学者有很大的帮助。
2021-08-24 22:29:34 1.79MB 图论 算法
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信息学奥赛一本通(C++版)
2021-08-22 22:10:28 367KB C++ 奥赛
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本软件是用来求解图论算法的可视化软件,修正了目前的bug。
2021-08-18 23:59:20 410KB 图论 软件
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本软件是用来求解图论算法的可视化软件,修正了目前的bug。
2021-07-30 11:56:48 411KB 图论 软件
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该软件是用来求解图论算法。其可求解的算法有:最短路径、最小生成树、拓扑排序、关键路径、最大流、最小费用最大流,利用最大流还可求解二部图的最大匹配。
2021-07-19 14:07:09 410KB
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作者: Jeremy Kepner / John Gilbert 出版社: Society for Industrial & Applied Mathematics 出版年: 2011-7-14 页数: 389 定价: USD 110.00 装帧: Hardcover ISBN: 9780898719901 Graphs are among the most important abstract data types in computer science, and the algorithms that operate on them are critical to modern life. Graphs have been shown to be powerful tools for modeling complex problems because of their simplicity and generality. Graph algorithms are one of the pillars of mathematics, informing research in such diverse areas as combinatorial optimization, complexity theory, and topology. Algorithms on graphs are applied in many ways in today s world - from Web rankings to metabolic networks, from finite element meshes to semantic graphs. The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance. Graph Algorithms in the Language of Linear Algebra is the first book to cover graph algorithms accessible to engineers and scientists not trained in computer science but having a strong linear algebra background, enabling them to quickly understand and apply graph algorithms. It also covers array-based graph algorithms, showing readers how to express canon
2021-06-27 17:38:10 3.93MB 图论,算法
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