Showing papers on "Prim's algorithm published in 2019"

Optimal Routing an Ungrounded Electrical Distribution System Based on Heuristic Method with Micro Grids Integration

Abstract: This paper proposes a three-layer model to find the optimal routing of an underground electrical distribution system, employing the PRIM algorithm as a graph search heuristic. In the algorithm, the first layer handles transformer allocation and medium voltage network routing, the second layer deploys the low voltage network routing and transformer sizing, while the third presents a method to allocate distributed energy resources in an electric distribution system. The proposed algorithm routes an electrical distribution network in a georeferenced area, taking into account the characteristics of the terrain, such as streets or intersections, and scenarios without squared streets. Moreover, the algorithm copes with scalability characteristics, allowing the addition of loads with time. The model analysis discovers that the algorithm reaches a node connectivity of 100%, satisfies the planned distance constraints, and accomplishes the optimal solution of underground routing in a distribution electrical network applied in a georeferenced area. Simulating the electrical distribution network tests that the voltage drop is less than 2% in the farthest node.

Registration Algorithm for Point Cloud Based on Normalized Cross-Correlation

Abstract: We propose a registration algorithm based on neighborhood similarity for 3D point clouds collected by optical measurement and without prior information. The algorithm first applies the improved minimum spanning tree (Prim algorithm) to classify the point cloud in order to obtain the topology information of the data. Specifically, vectors among root nodes and child nodes are processed, and the points on nodes are classified into different levels according to their scanning angle to simplify data and preserve the most representative points. Then, through the perspective conversion between 2D and 3D and according to the corresponding point set obtained by previous classification, the fast normalized cross-correlation (a 2D matching criterion) is applied to determine the relationship between initial characteristic points. Finally, distance constraints remove the errors between point pairs and allow calculating the registration parameters. Experimental results show that the algorithm has high registration accuracy and is suitable for point cloud data obtained by laser and structured light acquisition.

A spanning tree construction algorithm for industrial wireless sensor networks based on quantum artificial bee colony

Abstract: In industrial Internet, many intelligent applications are implemented based on data collection and distribution. Data collection and data distribution in the wireless sensor networks are very important, where the node topology can be described by the spanning tree for obtaining an efficient transmission. Classical algorithms in graph theory such as the Kruskal algorithm or Prim algorithm can only find the minimum spanning tree (MST) in industrial wireless sensor networks. Swarm intelligence algorithm can obtain multiple solutions in one calculation. Multiple solutions are very helpful for improving the reliability of industrial wireless sensor networks. In this paper, we combine quantum computing with artificial bee colony and design a spanning tree construction algorithm for industrial wireless sensor networks. Quantum computations are introduced into the onlooker bees search. Food source replacement strategy is improved. Finally, the algorithm is simulated and evaluated. The results show that the new proposed algorithm can obtain more alternative solutions and has a better performance in search efficiency.

A 5-approximation algorithm for the k-prize-collecting Steiner tree problem

Abstract: In this paper, we consider the k-prize-collecting Steiner tree problem (k-PCST), extending both the prize-collecting Steiner tree problem (PCST) and the k-minimum spanning tree problem (k-MST). In this problem, we are given a connected graph \(G = (V, E)\), a root vertex r and an integer k. Every edge in E has a nonnegative cost. Every vertex in V has a nonnegative penalty cost. We want to find an r-rooted tree F that spans at least k vertices such that the total cost, including the edge cost of the tree F and the penalty cost of the vertices not spanned by F, is minimized. Our main contribution is to present a 5-approximation algorithm for the k-PCST via the methods of primal–dual and Lagrangean relaxation.

Dynamic multi-keyword based search algorithm using modified based fully homomorphic encryption and Prim’s algorithm

Abstract: Cloud provides plenty of storage that makes enterprises to move their precious information/documents to the cloud. Since the user moves their valued data to the cloud, security is a major concern between storage service provider and user. To ascertain the security, the cryptography plays vital role in the searchable encryption based document. In this paper, Dynamic multi keyword based search Algorithm is proposed that contain modified fully homomophic encryption and prims Algorithm. Based on keyword frequency present in the document, keywords are sorted and built searchable index for keyword and files. The dynamic tree is constructed using prim‘s algorithm based on keyword and file. The encrypted files in the tree are indexed to keywords using two way Hash table for efficient search and retrival of documents. The files are encrypted using modified ring based fully homomorphic encryption. The experimental result shows that proposed work provides 80 and 86% encryption and decryption throughput and take less indexing time to index the files than existing RC4+.

A Graph Theory-Based Method for Regional Integrated Energy Network Planning: A Case Study of a China–U.S. Low-Carbon Demonstration City

Abstract: With the significant attention on global climate change, regional integrated energy systems (RIES) in low-carbon city planning has become one of the most important ways for global cities to achieve the goal of energy conservation and emission reduction. However, the planning strategy used in the primary stage of RIES establishment will greatly affect the system economy and environment. In view of the lack of planning guidance mechanisms for the large-scale RIES in China, a method for RIES preliminary overall planning, focused on energy types and use, is proposed in this paper. A graph theory-based mathematical optimal model was established with the lifetime costs of the whole system as the economic goal, and an improved Prim algorithm was put forward to solve the costs of the transmission and distribution network with the dynamic weight set of pipeline flow. The model was solved by an algorithm based on the idea of a dynamic minimum spanning tree and optimal path planning. The model and method were applied in a China–U.S. low-carbon demonstration city to verify feasibility and validity. The results could help us to comprehensively integrate regional energy and accurately plan future cities.

K Medoids Based Clustering Algorithm with Minimum Spanning Tree in Wireless Sensor Network

Abstract: Many Wireless Sensor Network named as (WSN) have the resource constrained sensor nodes, that are predictable to work autonomously for long-time, such as months/years.Because of there stricted accessibility of the power supply, the main worry in the WSN is energy preservation. Throughout previous phases of the development of WSN, the nodes were static & communication between any of 2 hubs was completed through utilizing the multi-hop pathway. Usually, the Minimum Spanning Tree named as (MST) utilized the optimum data aggregation tree for an energy-efficient routing. Earlier the consumption of energy condensed through the hop basis data transmission include the help of the Prim's Algorithm. In this article, K-Medoids clustering based algorithm utilized to create clusters & then tree creation to enhance the effectiveness of network. Simulation has been done on the tool of MATLAB & outcome display that the proposed work has better first dead node time.

Differential privacy-based data exception detection method

Abstract: The invention discloses a differential privacy-based data exception detection method. According to the method, the clustering is conducted firstly and then the exception detection is conducted. The method comprises the following steps of adding random noise to the weight of the edge in a minimum spanning tree generated by a prim algorithm by using a noise mechanism in the differential privacy so as to hide the relevance between data objects. Meanwhile, the method uses a judgment criterion of fusing dissimilarity and inverse similarity number to detect abnormality. By adopting the method, the problem that parameters need to be preset and the abnormal data selection is inaccurate in the traditional top-n method can be solved. The method provided by the invention has higher robustness and stronger adaptability, and experimental analysis of the simulation data set and the real data set shows that the method provided by the invention can effectively ensure the security of private data in anenvironment with non-uniform data distribution, improve the recall ratio of anomaly detection and reduce the misjudgment rate.

Fast Path-Oriented Strategy for Power System Restoration

Abstract: An effective power system restoration strategy plays an important role in speeding up the recovery of electricity supply in cases of major blackouts. Determining the start-up sequences of non black-start units (NBSUs) is a major concern in power system restoration and is usually formulated as an optimization problem and solved by optimization algorithms including evolutionary algorithms which usually suffer from slow convergence. So far, analytical methods have not yet been widely adopted in formulating power system restoration strategies, and the majority of which are unit-oriented. However, the operation of a transmission network can hardly be integrated into the unit-oriented restoration strategies, thus the iterations between determining the start-up sequences of NBSUs and optimizing the structure of the transmission network concerned become inevitable. In this paper, a graph-theory-based path-oriented power system restoration strategy is proposed for fast, dynamic and highly adaptive power system restoration. A specified minimum spanning tree (SMST) is introduced to model the path-oriented restoration problem considering practical power system constraints, and a modified Prim's algorithm is proposed to generate the SMST. The optimality of the proposed SMST strategy and the performance of the modified Prim's result are also demonstrated. Finally, the feasibility and efficiency of the developed model and method are verified with a modified version of the New England 10-unit 39-bus power system and an actual power system in Guangdong, China.

Unmanned aerial vehicle situation data clustering method based on combined multi-target pigeon group optimization

Abstract: The invention discloses an unmanned aerial vehicle situation data clustering method based on combined multi-target pigeon group optimization. The method comprises the following steps: loading a data set; calculating a difference matrix and an adjacent matrix of the data set; solving a minimum spanning tree by using a Prim algorithm; dividing frontier sets in the minimum spanning tree into a strongconnection frontier set and a weak connection frontier set; decoding the strong connection frontier set, and pre-calculating clustering generating an initial pigeon group, decoding the pigeon group to obtain a clustering result, and then evaluating the initial pigeon group by using tightness and continuity; performing non-dominated sorting on the initial pigeon group, and determining a global historical optimal position and a central position of the pigeon group at the current moment; and updating the position and the speed of the pigeon group, and decoding the position of the pigeon group toobtain a clustering result, updating the global historical optimal position and the central position of the pigeon group, and maintaining the process till a terminating condition is satisfied. The method of the invention is easy to realize, reduces the calculation load, lowers the dimensionality of a decision space, can search an optimal solution more easily, and has relatively high capacity foradapting to different clustering demands.

Discrete Mathematics: Graph Algorithms, Algebraic Structures, Coding Theory, and Cryptography

Abstract: Conveying ideas in a user-friendly style, this book has been designed for a course in Applied Algebra. The book covers graph algorithms, basic algebraic structures, coding theory and cryptography. It will be most suited for senior undergraduates and beginning graduate students in mathematics and computer science as also toindividuals who want to have a knowledge of the below-mentioned topics. Provides a complete discussion on several graph algorithms such as Prims algorithm and Kruskals algorithm for sending a minimum cost spanning tree in a weighted graph, Dijkstras single source shortest path algorithm, Floyds algorithm, Warshalls algorithm, Kuhn-Munkres Algorithm. In addition to DFS and BFS search, several applications of DFS and BFS are also discussed. Presents a good introduction to the basic algebraic structures, namely, matrices, groups, rings, fields including finite fields as also a discussion on vector spaces and linear equations and their solutions. Provides an introduction to linear codes including cyclic codes. Presents a description of private key cryptosystems as also a discussion on public key cryptosystems such as RSA, ElGamal and Miller-Rabin. Finally, the Agrawal-KayalSaxena algorithm (AKS Algorithm) for testing if a givenpositive integer is prime or not in polynomial time is presented- the first time in a textbook. Two distinguished features of the book are: Illustrative examples have been presented throughout the book to make the readers appreciate the concepts described. Answers to all even-numbered exercises in all the chapters are given.

An Improved Prim Algorithm for Connection Scheme of Last Train in Urban Mass Transit Network

Abstract: In the network operation stage of urban mass transit, the connection relations between lines can effectively improve travel accessibility. As the last opportunity to travel on the same day, whether the last train can achieve transfer will directly affect passengers’ travel experiences. It is an important work to make the connection scheme of the last train, which needs to take the network structure, the trend, and the volume of passenger flow into overall consideration. This paper analyzes the characters of the last train connection, including the connection structure and the accessible form. Then, we establish a scheme model and define the objectives, the constraints, and the decision data source, and transform it into a graph theory problem. Taking an urban mass transit network as an example, we demonstrate the solution process by using an improved Prim algorithm. Finally, the main aspects and methods of initial scheme optimization are proposed.

Tree Based EM-Prim's Algorithm For Energy Efficient Networking

Abstract: Network and networking equipment's are one of the biggest contributors to the consumption of energy. To reduce energy consumption in networks, many techniques and algorithms have been developed over the years. But most of the algorithms require complicated computation thus requiring more time and energy. Here, we concentrated on the problem of reducing the number of active links when there is less load on the network. We propose a simple and elegant solution to the problem. We propose to use our EM-Prim's instead of using OSPF, a shortest path-finding algorithms which is used in most cases. Our EM-Prim's algorithm is a tree-based solution to reduce the number of links in a topology. We compared our algorithm with modified Dijkstra's algorithm and tested it against different topologies in case of different demand sizes in this paper and found significant improvements in the reduction of energy in networks.

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.

A Linear Time Algorithm for Finding Minimum Spanning Tree Replacement Edges.

Abstract: Given an undirected, weighted graph, the minimum spanning tree (MST) is a tree that connects all of the vertices of the graph with minimum sum of edge weights. In real world applications, network designers often seek to quickly find a replacement edge for each edge in the MST. For example, when a traffic accident closes a road in a transportation network, or a line goes down in a communication network, the replacement edge may reconnect the MST at lowest cost. In the paper, we consider the case of finding the lowest cost replacement edge for each edge of the MST. A previous algorithm by Tarjan takes $O(m \alpha(m, n))$ time, where $\alpha(m, n)$ is the inverse Ackermann's function. Given the MST and sorted non-tree edges, our algorithm is the first that runs in $O(m+n)$ time and $O(m+n)$ space to find all replacement edges. Moreover, it is easy to implement and our experimental study demonstrates fast performance on several types of graphs. Additionally, since the most vital edge is the tree edge whose removal causes the highest cost, our algorithm finds it in linear time.

User group grouping method and device based on Prim algorithm in two-stage precoding

Abstract: The invention discloses a user group grouping method and a device based on a Prim algorithm in two-stage precoding. The method comprises the following steps: constructing a large-scale MIMO frequencydivision duplex downlink system based on channel statistics; the system comprises a multi-antenna single base station signal sending end and a plurality of single-antenna user terminals. Based on long-term channel statistical characteristics, characteristic beams are selected for eigenvalue decomposition, a minimum mean square error coding method is adopted for two-stage precoding, and a pluralityof corresponding user groups are obtained through division; solving the signal propagation angle range overlapping degree of different user groups in the plurality of user groups obtained by division, and converting the signal propagation angle range overlapping degree into a corresponding undirected weighted graph; and performing optimal user group grouping by adopting a Prim algorithm based onthe undirected weighted graph. According to the scheme, optimal scheduling can be carried out after two-stage precoding, and the problem that signal propagation angle ranges of different user groups are overlapped is solved.

A P-Cycle Protection Algorithm Based on Capacity Balance for Power Optical Communication Multicast Service

Abstract: Aiming at the protection problem of single link/node in the existing power optical communication network multicast service, a p-cycle protection algorithm is proposed. The protection algorithm firstly uses the optimized prim algorithm to generate a multicast tree, and then generates a p-cycle to protect the entire multicast tree through a heuristic shortest P-cycle construction algorithm, and uses a capacity balancing mechanism in the simulation of the protection algorithm to reduce the blocking rate. The simulation results show that the proposed algorithm's resource redundancy and network blocking rate is lower than the existing Hamiltonian ring protection algorithm. It has practical significance for improving the survivability and stability of optical communication networks.

A network planning method for underground logistics system based on 0-1 programming and prim algorithm

Abstract: A network planning method for underground logistics system based on 0-1 programming and prim algorithm, includes such steps as selecting secondary node and auxiliary region, using prim algorithm to construct route of primary node and secondary node and its auxiliary point, selecting tunnel and track specifications, arranging transportation vehicle type and vehicle number, and completing logisticssystem network planning and output result; On the basis of satisfying different conditions such as service scope, ensuring ground freight volume receiving and dispatching, alleviating traffic congestion degree and the like, the method obtains the objective programming expression of nodes at all levels, and adjusts under the requirement of ensuring full coverage of traffic congestion area accordingto the principle of high and low congestion index and uniform distribution of regional points. Prim algorithm is used to establish track connection, which ensures the shortest route and the lowest cost Traffic congestion is reduced and the solving process is simplified, which provides a whole set of methods for the construction of underground logistics system network and can be popularized according to the characteristics of freight distribution in each target area.

Measurement configuration method for harmonic state estimation

Abstract: The invention discloses a measurement configuration method for harmonic state estimation in the technical field of power engineering, and aims to solve the technical problem that the harmonic state estimation result is not ideal due to the lack of an accurate common time reference in the prior art. The invention relates to a measurement configuration method for harmonic state estimation. The method comprises the following steps of: calculating a sensitive factor of the change of a harmonic branch current relative to an injected harmonic current; calculating each harmonic weight coefficient byemploying a G1 method, and comprehensively obtaining comprehensive sensitive factors of all harmonic branches under the action of each injected harmonic current; taking the comprehensive sensitivity factor as the weight coefficient of each harmonic branch, taking each bus as an initial search point, and obtaining a tree with the maximum weight coefficient by utilizing a maximum spanning tree theorem Prim algorithm; and forming a plurality of groups of considerable measurement point configuration schemes meeting the maximum spanning tree topology by combining the PMU configuration characteristics, and determining an optimal configuration scheme. The method can achieve synchronous measurement of the plurality of measuring points, so that the harmonic state estimation result is more accurate,and the method has better economical efficiency and practicability.