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.

An Approach of Community Search with Minimum Spanning Tree Based on Node Embedding

Abstract: Community search is a query-oriented variant of community detection problem, and the goal is to retrieve a single community from a given set of nodes. Most of the existing community search methods adopt handcrafted features, so there are some limitations in applications. Our idea is motivated by the recent advances of node embedding. Node embedding uses deep learning method to obtain feature representation of nodes directly from graph structure automatically and offers a new method to measure the distance between two nodes. In this paper, we propose a two-stage community search algorithm with a minimum spanning tree strategy based on node embedding. At the first stage, we propose a node embedding model NEBRW and map nodes to the points in a low-dimensional vector space. At the second stage, we propose a new definition of community from the distance viewpoint, transform the problem of community search to a variant of minimum spanning tree problem, and uncover the target community with an improved Prim algorithm. We test our algorithm on both synthetic and real-world network datasets. The experimental results show that our algorithm is more effective for community search than baselines.

The Topological Detection Algorithm of Object Arrays in Noisy Context Based on Fuzzy Spatial Information Fusion and Prim Algorithm

Abstract: Most computer vision methods deal with the single object recognition problem. If an object is so small that little features can be used to support recognition procedure, the relationship between multi-objects could be helpful. In many cases, small objects are likely to be arranged by some regular shapes. To recognize these arrays, the paper presents a spatial topology detection algorithm. We call it as S-Prim (Spatial Prim) algorithm which is based on classic Prim algorithm, and integrates the fuzzy spatial information. The algorithm evaluates the spatial distribution regularity among neighboring nodes by back searching the path in the found tree when it is growing, and controls its growing direction according to some fuzzy rules to find out the most likely regular spatial topology. The detected tree can be considered as a spanning tree constrained by topological structures.

Power impedance topological graph generation method and system for power distribution area

Abstract: The invention discloses a power impedance topological graph generation method and system for a power distribution area, and belongs to the technical field of power distribution areas. Current line impedance identification is large in calculated amount and long in required time. The invention relates to a power impedance topological graph generation method and system for a power distribution area,and the method comprises the steps: firstly obtaining the A/B/C three phases of a power distribution transformer side and the time sequence voltage data of each user load node, determining the phase relation of each load node through a K-means clustering method, and constructing a feature coefficient matrix for the divided A/B/C three phases; generating a single-phase topological adjacency matrixfor the characteristic coefficient matrix by adopting a prim algorithm, and finally fusing the obtained three-phase topological adjacency matrix of the transformer area with line impedance informationand geographic information coordinates to form an electric power information map of the whole power distribution transformer area; and the problems that in a traditional topology generation and parameter identification method, the hardware cost is too high, the node load phase cannot be determined, and the calculation time is long can be solved.

Distributed minimum spanning tree based information exchange policy for distributed systems

Abstract: Distributed system has an inherent problem of unevenly distributed load. The possible solution to this problem is load balancing. For the above purpose it is very important to have updated information about the load status of the nodes comprising the system. This work proposes a Distributed Minimum Spanning Tree based Information Exchange (DMSTIE) strategy. The strategy helps in collecting the load information of the nodes through the edges formed during the Distributed Minimum Spanning Tree (DMST) process. Based on the information about the system state various load balancing approach can be applied for transferring extra load over the underutilized nodes. An MST based approach results in the information collection and eventually dispatch of load efficiently in terms of communication and computation.

PST-Prim Heuristic for the Open Vehicle Routing Problem

Abstract: The objective of this paper is to present and demonstrate the validation of the functioning of a recursive heuristic based on the algorithm of Prim and that gives solution to the open vehicle routing problem (OVRP). Today this problem has a considerable approach, so a literature review that sets the theoretical basis for the work, is made. The OVRP is formally shown and the covering tree with paths (PST) is defined. Next, the subroutine that follows the PST-Prim algorithm is indicated to construct the PST of any graph, as well as the modification that must be made to arrive at the PST-Prim Heuristic that gives solution to the OVRP. An illustrative example of the construction of PST to an example graph is presented. To illustrate and validate its effectiveness of the heuristic, it is used to solve 17 widely used problems to verify and compare the behavior of this type of algorithms. In addition, the PST-Prim heuristic performance is compared with other seven algorithms; the value of the objective function and the computation time for each algorithm on the 17 instances is presented. The PST-Prim propose the best solutions on 12 of the 17 instances. At the end, the performance, use and importance of the heuristic is discussed.