Prim's algorithm

About: Prim's algorithm is a research topic. Over the lifetime, 775 publications have been published within this topic receiving 17971 citations. The topic is also known as: DJP algorithm & Jarník algorithm.

IKCAP: An Improved K-means Clustering Algorithm Based on Prim ⋆

Abstract: In k-means clustering algorithm, it remains a problem that the initial cluster centers are selected randomly. To deal with the randomness problem, the Prim minimum spanning tree is introduced to the initial center selection of K-means clustering algorithm. Firstly, the prim method is used to find the minimum spanning tree for the randomly generated points, then a group of points are selected as the initial center which has the maximum sum of the weights and all weights have little difference. Finally, we propose an improved K-means clustering algorithm based on prim. Simulation results show that, compared with NKM (Normal K-Means) algorithm, our algorithm improves the accuracy and reduces the data iterations.

Penerapan teori graf untuk menyelesaikan masalah minimum spanning tree (mst) menggunakan algoritma kruskal

Abstract: One of useful graph theory to solve the real problems is Minimum Spanning Tree (MST). MST is network optimization problems that can be applied in many fields such as transportations problems and communication network design (Gruber and Raidl, 2005). MST begins from tree namely a connected graph has no circuits. From the graph, there is a sub-graph that has all the vertex or spanning tree. If that graph has the weight/cost, then the spanning tree that has the smallest weight/cost is called Minimum Spanning Tree. Basic algorithm used to determine the MST is Kruskal’s algorithm. This algorithm is known as one of the best algorithms for the optimization problems, especially for MST. In this paper is developed a source code program to determine MST using Kruskal’s algorithm and then implemented on several data representing a complete graph.

A note on the uniform edge-partition of a tree 1

Abstract: We study the problem of uniformly partitioning the edge set of a tree with n edges into k connected components, where kn. The objective is to minimize the ratio of the maximum to the minimum number of edges of the subgraphs in the partition. We show that, for any tree and k • 4, there exists a k-split with ratio at most two. (Proofs for k = 3 and k = 4 are omitted here.) For general k, we propose a simple algorithm that finds a k-split with ratio at most three in O(nlogk) time. Experimental results on random trees are also shown.

Algorithm of all vertices-constrained shortest path

Abstract: An algorithm for all vertices-constrained shortest paths is put forward bases on some special data structures,such as inverse adjacency list and uses a minimum spanning tree and the pointer list that marks leaves of the trees.The theoretical analysis show that the efficiency of this algorithm is high,and is that it is very simple and very easy to be described,fulfilled and understood.And using a C program testifies its quality.

Constant-time Algorithms for Minimum Spanning Tree and Related Problems on Processor Array with Reconfigurable Bus Systems

Abstract: A processor array with a reconfigurable bus system is a parallel computation model that consists of a processor array and a reconfigurable bus system. In this paper, a constant-time algorithm is proposed on this model for finding the cycles in an undirected graph. We can use this algorithm to decide whether a specified edge belongs to the minimum spanning tree of the graph or not. This cycle-finding algorithm is designed on a two-dimensional n×n processor array with a reconfigurable bus system, where n is the number of vertices in the graph. Based on this cycle-finding algorithm, the minimum spanning tree problem and the spanning tree problem can be solved in O(1) time by using fewer processors than before, O(n × m × n) and O(n3) processors respectively. This is a substantial improvement over previous known results. Moreover, we also propose two constanttime algorithms for solving the minimum spanning tree verification problem and spanning tree verification problem by using O(n3) and O(n2) processors, respectively.