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Relevant bibliographies by topics / Algorytm Kruskala

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Academic literature on the topic 'Algorytm Kruskala'

Author: Grafiati

Published: 24 April 2022

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Journal articles on the topic "Algorytm Kruskala"

1

Paryati and Krit Salahddine. "The Implementation of Kruskal’s Algorithm for Minimum Spanning Tree in a Graph." E3S Web of Conferences 297 (2021): 01062. http://dx.doi.org/10.1051/e3sconf/202129701062.

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Kruskal’s Algorithm is an algorithm used to find the minimum spanning tree in graphical connectivity that provides the option to continue processing the least-weighted margins. In the Kruskal algorithm, ordering the weight of the ribs makes it easy to find the shortest path. This algorithm is independent in nature which will facilitate and improve path creation. Based on the results of the application system trials that have been carried out in testing and comparisons between the Kruskal algorithm and the Dijkstra algorithm, the following conclusions can be drawn: that a strength that is the existence of weight sorting will facilitate the search for the shortest path. And considering the characteristics of Kruskal’s independent algorithm, it will facilitate and improve the formation of the path. The weakness of the Kruskal algorithm is that if the number of nodes is very large, it will be slower than Dijkstra’s algorithm because it has to sort thousands of vertices first, then form a path.

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2

Paryati and Krit Salahddine. "The Implementation of Kruskal’s Algorithm for Minimum Spanning Tree in a Graph." MATEC Web of Conferences 348 (2021): 01001. http://dx.doi.org/10.1051/matecconf/202134801001.

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Abstract:

Kruskal’s Algorithm is an algorithm used to find the minimum spanning tree in graphical connectivity that provides the option to continue processing the least-weighted margins. In the Kruskal algorithm, ordering the weight of the ribs makes it easy to find the shortest path. This algorithm is independent in nature which will facilitate and improve path creation. Based on the results of the application system trials that have been carried out in testing and comparisons between the Kruskal algorithm and the Dijkstra algorithm, the following conclusions can be drawn: that a strength that is the existence of weight sorting will facilitate the search for the shortest path. And considering the characteristics of Kruskal’s independent algorithm, it will facilitate and improve the formation of the path. The weakness of the Kruskal algorithm is that if the number of nodes is very large, it will be slower than Dijkstra’s algorithm because it has to sort thousands of vertices first, then form a path.

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3

Choi, Myeong-Bok, and Sang-Un Lee. "An Efficient Implementation of Kruskal's and Reverse-Delete Minimum Spanning Tree Algorithm." Journal of the Institute of Webcasting, Internet and Telecommunication 13, no. 2 (2013): 103–14. http://dx.doi.org/10.7236/jiibc.2013.13.2.103.

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4

Li, Haiming, Qiyang Xia, and Yong Wang. "Research and Improvement of Kruskal Algorithm." Journal of Computer and Communications 05, no. 12 (2017): 63–69. http://dx.doi.org/10.4236/jcc.2017.512007.

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5

Zakiah, Nina. "DIAGRAM ALIR ALGORITMA KRUSKAL DALAM MENENTUKAN MINIMUM SPANNING TREE." JURNAL MATHEMATIC PAEDAGOGIC 5, no. 2 (2021): 151–57. http://dx.doi.org/10.36294/jmp.v5i2.1977.

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AbstractThe flow chart of the minimum spanning tree is represented in a weight matrix as a form of development of the link matrix. Determining the minimum spanning tree in this journal uses the Kruskal algorithm and is implemented in the form of a flow chart. This journal is a study of theories regarding the minimum spanning tree determination problem. With the problem approach, namely: graph theory, trees, determination of Minimum spanning tree, Kruskal's algorithm and flow diagrams. Furthermore, it is implemented in the flowchart of determining the Minimum spanning tree. Keywords: Minimum spanning tree, Kruskal's Algorithm, flow chart

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6

Wattimena, Abraham Z., and Sandro Lawalatta. "APLIKASI ALGORITMA KRUSKAL DALAM PENGOTIMALAN PANJANG PIPA." BAREKENG: Jurnal Ilmu Matematika dan Terapan 7, no. 2 (2013): 13–18. http://dx.doi.org/10.30598/barekengvol7iss2pp13-18.

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Algoritma Kruskal dalam pencarian pohon merentang minimum dapat di aplikasikan pada jaringan pipa yang terpasang di lokasi jalan Ina Tuni Karang Panjang Ambon. Skripsi ini adalah penelitian yang bersifat studi kasus dan merupakan suatu aplikasi graf dalam kehidupan sehari-hari. Permasalahan yang dibahas dalam skripsi ini adalah panjang pipa yang terpasang pada jalan Ina Tuni Ambon sepanjang 1448 meter sedangkan panjang pipa dengan menggunakan algoritma Kruskal sepanjang 1026 meter. Dalam skripsi ini dititik beratkan pada pengoptimalan panjang pipa yang merupakan salah satu masalah pohon merentang minimum pada graf. Jaringan pipa akan direpresentasikan ke dalam bentuk graf terhubung, tak berarah dan berbobot.

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7

Aissa, Mohamed, Adel Ben Mnaouer, Rion Murray, and Abdelfettah Belghith. "New Strategies and Extensions in Kruskal’s Algorithm in Multicast Routing." International Journal of Business Data Communications and Networking 7, no. 4 (2011): 32–51. http://dx.doi.org/10.4018/jbdcn.2011100103.

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Multimedia applications are expected to guarantee end-to-end quality of service (QoS) and are characterized by stringent constraints on delay, delay-jitter, bandwidth, cost, and so forth. The authors observe that Kruskal’s algorithm is limited to minimal (maximal) spanning unconstrained tree. As such, the authors extend Kruskal’s algorithm to incorporate the delay bound constraint. Consequently, a novel algorithm is proposed, called EKRUS (Extended Kruskal), for constructing multicast trees. The EKRUS’ distinguishing features consists of a better management of Kruskal’s priority queues, and in the provision of edge priority aggregation. Preliminary results show that the proposed EKRUS algorithm performs as well as the best-known algorithms (such as the DDMC, DMCTc algorithms) while exhibiting reduced complexity. The authors conducted an intensive analysis and evaluations of different strategies of assigning edges into the classes of the queue as well as edge selection. As a result, the EKRUS algorithm was further extended with different edge assignment and selection strategies. Through extensive simulations, the authors have evaluated various versions of the EKRUS and analyzed their performance under different load conditions.

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8

Xiao, Hai. "RGV dynamic scheduling model based on kruskal algorithm." IOP Conference Series: Materials Science and Engineering 612 (October 19, 2019): 032028. http://dx.doi.org/10.1088/1757-899x/612/3/032028.

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9

Granera, Julia Argentina, Victor Manuel Valdivia, and Maria Elena Blandón Dávila. "Aplicación informática KPTS (Kruskal, Prim, Tabu Search)." Revista Científica de FAREM-Estelí, no. 17 (May 9, 2016): 81–90. http://dx.doi.org/10.5377/farem.v0i17.2616.

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En este artículo se muestra la aplicación de una herramienta informática basada en teoría de grafos para analizar y resolver problemas de las rutas más cortas, utilizando los algoritmos de Prim, Kruskal y de búsqueda local de Tabú Search. Para el desarrollo de esta aplicación se utilizaron los siguientes elementos: Visual Studio 2010, librería GraphSharp y librería QuickGraph. Para la creación de esta herramienta, se estableció una estructura de clases que diera soporte a los gráficos: 1) PocGraph: representa el grafo; 2) PocEdge: representa las aristas del grafo; y 3) PocVertex: representa los nodos o vértices del grafo. Tanto el método de Kruskal como Prim generan un árbol mínimo recubridor del grafo, el cual consiste en un subgrafo del original. El algoritmo de Prim se trabajó con el objetivo de encontrar el árbol recubridor más corto; mientras que el algoritmo de Kruskal, con la finalidad de hallar el árbol minimal a partir de instancias TSP. El método de Tabú Search se aplica para encontrar el mínimo camino cerrado que une todos los vértices o nodos. Se diseñó el algoritmo de Tabú Search para minimizar las rutas partiendo de una solución inicial la cual se va modificando hasta obtener el resultado.

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10

Mahardika, Fajar. "Penerapan Teori Graf Pada Jaringan Komputer Dengan Algoritma Kruskal." Jurnal Informatika: Jurnal Pengembangan IT 4, no. 1 (2019): 48–53. http://dx.doi.org/10.30591/jpit.v4i1.1032.

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