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Description: 用树的应用模拟铁路查询功能。掌握图的邻接表的定义及应用,能够熟练使用邻接表。加强对map容器的理解，能够熟练使用map容器，复习集合和字典的相关知识。理解最短路径问题，并使用Dijkstra算法解决最短路径问题。掌握线形表的使用，并理解优先队列解决问题的过程。利用栈解决需要逆向输出的问题。
-Application of simulation using the tree railway inquiry function. Master graph adjacency list of definitions and applications, able to skillfully use the adjacency list. Enhance the understanding of map containers, able to skillfully use the map container, collection and review of the relevant knowledge dictionary. Understanding of the shortest path problem, and use the Dijkstra shortest path algorithm to solve the problem. To master the use of linear form, and understand the priority queue problem-solving process. Use the stack to resolve the issue of the need to reverse the output.
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Size: 2048 |
Author: sunfuquan |
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Description: 图的大部分实现 图的深度优先周游 图的广度优先周游 由队列方式实现的拓扑排序 由深度优先搜索方式实现的拓扑排序 单源最短路径(Dijkstra算法) 每对顶点之间的最短路径(Floyd算法) 最小支撑树(Prim算法) 最小支撑树(Kruskal算法)-Figure most of the implementation diagram of the depth-first breadth-first tour travel map be achieved by the topological sort the queue depth-first search be achieved by the topological sorting single-source shortest path (Dijkstra algorithm) between each pair of vertices the shortest path (Floyd Algorithm ) minimum spanning tree (Prim algorithm) minimum spanning tree (Kruskal algorithm)
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Size: 10240 |
Author: fzkj |
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Description: Dijkstra算法经典实现,计算节点最短路径 -Dijkstra implementation
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Size: 3072 |
Author: 张 |
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Description: 实现的是所有边权为正的最短路径算法的Dijkstra和优先队列Dijstra堆算法-The right of all sides to achieve a positive Dijkstra shortest path algorithm and the priority queue heap algorithm Dijstra
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Size: 1024 |
Author: 张佳静 |
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Description: 最短路径_dijkstra堆优化+优先队列-dijkstra priority queue
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Size: 1024 |
Author: 蔡亚 |
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Description: Johson算法是目前最高效的在无负环可带负权重的网络中求所有点对最短路径的算法. Johson算法是Bellman-Ford算法, Reweighting(重赋权重)和Dijkstra算法的大综合. 对每个顶点运用Dijkstra算法的时间开销决定了Johnson算法的时间开销. 每次Dijkstra算法(d堆PFS实现)的时间开销是O( E * lgd(V) ). 其中E为边数, V为顶点数, d为采用d路堆实现优先队列ADT. 所以, 此种情况下Johnson算法的时间复杂度是O( V * E * lgd(V) ).-The Johson algorithm is currently the most efficient of the network without negative ring can with negative weights seek all points of the shortest path algorithm. Johson algorithm Bellman-Ford algorithm Reweighting (re-empower the weight) and Dijkstra algorithm for the large integrated. For eachtime overhead of the vertices using Dijkstra algorithm to determine the time of the Johnson algorithm overhead each Dijkstra algorithm (d-heap PFS), time overhead is O (E* lgd (V)) where E is the number of edges, V verticesd d Lu heap priority queue the ADT. this case the Johnson algorithm time complexity is O (V* E* lgd (V)).
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Size: 2048 |
Author: wwll |
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Description: Johson算法是目前最高效的在无负环可带负权重的网络中求所有点对最短路径的算法. Johson算法是Bellman-Ford算法, Reweighting(重赋权重)和Dijkstra算法的大综合. 对每个顶点运用Dijkstra算法的时间开销决定了Johnson算法的时间开销. 每次Dijkstra算法(d堆PFS实现)的时间开销是O( E * lgd(V) ). 其中E为边数, V为顶点数, d为采用d路堆实现优先队列ADT. 所以, 此种情况下Johnson算法的时间复杂度是O( V * E * lgd(V) ).-The Johson algorithm is currently the most efficient of the network without negative ring can with negative weights seek all points of the shortest path algorithm. Johson algorithm Bellman-Ford algorithm Reweighting (re-empower the weight) and Dijkstra algorithm for the large integrated. For eachtime overhead of the vertices using Dijkstra algorithm to determine the time of the Johnson algorithm overhead each Dijkstra algorithm (d-heap PFS), time overhead is O (E* lgd (V)) where E is the number of edges, V verticesd d Lu heap priority queue the ADT. this case the Johnson algorithm time complexity is O (V* E* lgd (V)).
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Size: 3072 |
Author: wwll |
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Description: 优先队列实现dijkstra算法C++代码，如何使用-algorithms: Priority queue dijkstra algorithm C++ code ，and how to use
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Size: 1024 |
Author: 褚炜雯 |
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Description: NS (Version 2) is an open source network simulation tool. It is an object oriented, discrete event driven simulator written in C++ and Otcl. The primary use of NS is in network researches to simulate various types of wired/wireless local and wide area networks to implement network protocols such as TCP and UPD, traffic source behavior such as FTP, Telnet, Web, CBR and VBR, router queue management mechanism such as Drop Tail, RED and CBQ, routing algorithms such as Dijkstra, and many more. -NS (Version 2) is an open source network simulation tool. It is an object oriented, discrete event driven simulator written in C++ and Otcl. The primary use of NS is in network researches to simulate various types of wired/wireless local and wide area networks to implement network protocols such as TCP and UPD, traffic source behavior such as FTP, Telnet, Web, CBR and VBR, router queue management mechanism such as Drop Tail, RED and CBQ, routing algorithms such as Dijkstra, and many more.
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Size: 536576 |
Author: mahadev gawas |
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Description: NS (Version 2) is an open source network simulation tool. It is an object oriented, discrete event driven simulator written in C++ and Otcl. The primary use of NS is in network researches to simulate various types of wired/wireless local and wide area networks to implement network protocols such as TCP and UPD, traffic source behavior such as FTP, Telnet, Web, CBR and VBR, router queue management mechanism such as Drop Tail, RED and CBQ, routing algorithms such as Dijkstra, and many more. -NS (Version 2) is an open source network simulation tool. It is an object oriented, discrete event driven simulator written in C++ and Otcl. The primary use of NS is in network researches to simulate various types of wired/wireless local and wide area networks to implement network protocols such as TCP and UPD, traffic source behavior such as FTP, Telnet, Web, CBR and VBR, router queue management mechanism such as Drop Tail, RED and CBQ, routing algorithms such as Dijkstra, and many more.
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Size: 9216 |
Author: mahadev gawas |
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Description: 提出一种新型的Dijkstra改进算法，具有高效性．其改进分3个方面：采用邻接表作为道路网络拓扑的存储结构；利用二叉堆实现优先队列；根据节点的分布情况将搜索过程分为几个阶段，引入了动态限制搜索区域机制．最后在实际道路网络中的测试及仿真结果表明了改进算法的可行性和优越性． -Dijkstra proposes a new improved algorithm with high efficiency. Improved three aspects: the adjacent table as the storage structure of the road network topology using binary heap priority queue node distribution of the search process is divided into several stages, the introduction of dynamic limit the search to regional mechanisms. Finally, the actual road network testing and simulation results show the feasibility and advantages of the improved algorithm.
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Size: 313344 |
Author: 请问 |
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Description: 图论的各种最短路算法,竞赛用
包括dijkstra、Bellman-Ford（SPFA）、Floyd-Warshall、优先队列的应用等-A variety of graph theory shortest path algorithm, racing including dijkstra, Bellman-Ford (SPFA), Floyd-Warshall, the application of the priority queue
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Size: 4096 |
Author: Flandre·Scarlet |
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Description: 设图的顶点大于1个，不超过30个，每个顶点用一个编号表示（如果一个图有n个顶点，则它们的编号分别为0, 1, 2, 3, …, n-1）。
此题为求有向网中顶点间最短路径问题，可建立以票价为权的邻接矩阵，用Dijkstra算法求最短路径长度。
Dijkstra算法中有一个辅助向量D，表示当前所找到的从源点到其它点的最短路径长度。因为每次都要在D中找最小值，为提高性能，用最小值堆的优先队列存储D值。
-Let the vertex is greater than 1, no more than 30, with a number that each vertex (if a graph with n vertices, their numbers are 0, 1, 2, 3, ..., n-1). This network entitled to seek a shortest path between vertices, we can establish the right of the fare for the adjacency matrix, using Dijkstra' s algorithm for the shortest path length. Dijkstra' s algorithm has an auxiliary vector D, the found that the current from the source point to the other points of the shortest path length. Because every time to find the minimum value in the D, to improve performance, with the minimum heap priority queue storage D values.
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Size: 911360 |
Author: 杜小方 |
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Description: ,更新：使用优先级队列实现的迪杰斯特拉算法，里面有个小对战游戏主要程序部分示例-Update: Dijkstra algorithm using priority queue implementation, there are a small part of the sample program main battle game
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Size: 11264 |
Author: stvh |
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Description: 更新：使用优先级队列实现的迪杰斯特拉算法，里面有个小对战游戏主要程序部分示例-Dijkstra algorithm using priority queue implementation, there are a small part of the sample program main battle game
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Size: 13312 |
Author: stvh |
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Description: 更新：使用优先级队列实现的迪杰斯特拉算法，里面有个小对战游戏主要程序部分示例-Dijkstra algorithm using priority queue implementation, there are a small part of the sample program main battle game
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Size: 14336 |
Author: stvh |
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Description: Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.-Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.
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Size: 1024 |
Author: Carabian Ovidiu |
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Description: 西安电子科技大学算法上机第三题，基于最小优先队列的迪杰斯特拉算法的改进(Improvement of Dijkstra algorithm based on minimum priority queue)
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Size: 1079296 |
Author: 有什么不妥
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Description: 使用优先级队列完成Dijkstra算法，使得寻找节点的时间复杂度为O（log|V|）(Using the priority queue to complete the Dijkstra algorithm)
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Size: 2048 |
Author: 不到终站 |
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