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11 articles for “spanning tree”
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Graph Sampling by Spanning Tree under Stratified Setup
Abstract: The sampling theory and its methodologies are based on assumption that the population under survey is of individuals and respondents have provided the answer of questions asked. When population is of graphical structure like containing nodes and edge links then it is complicated to apply the usual sampling procedures. Spanning tree is specified type of a graph, which is always connected with all nodes and becomes a sub-graph. Assume that …
Published in Research & Reviews : Journal of Statistics · Vol. 5, Issue 2, 2016 · pp. 11–31 Read article
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Fuzzy Minimum Spanning Tree Problem: A Greedy Algorithm using Quasi-Gaussian Fuzzy Weights
Abstract: The classical Minimum Spanning Tree Problem (MST) deals with determining the spanning tree in a given undirected graph G(V, E) for which the sum of the weights assigned to the edges is minimum. The weights assigned to the edges are real numbers representing parameters like demand, cost, link capacity and distance which are not naturally precise and the uncertainty involved can be modelled using fuzzy numbers. There are several types …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 1, Issue 3, 2014 · pp. 15–22 Read article
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Applying Kruskal's Algorithm in Supply Chain Management for Cost-Effective Network Optimization
Abstract: Transportation route optimization and cost reduction are major difficulties in today's dynamic and complicated supply chain systems. To produce economical and effective network designs, this study investigates the use of Kruskal's algorithm for supply chain network optimization. The algorithm guarantees that all supply chain nodes, including delivery hubs, warehouses, and distribution centers, relate to the lowest possible total transportation cost by building the minimum spanning tree (MST). The study shows …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 49–54 Read article
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Applications of Graph Theory in Computer Science
Abstract: Graph theory, a branch of mathematics, has found broad applications in different areas, especially in computer science. This study inspects the basic concepts of graph theory and its different applications in computer science. It talks about the role of graphs in modelling real-world networks, algorithmic problem-solving, optimization, data structures, network analysis, and other significant areas within the domain of computer science. Through different illustrations and case studies, this study aims …
Published in Journal of Open Source Developments · Vol. 10, Issue 3, 2023 · pp. 30–35 Read article
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Extracting High Dimensional Data by Using Fast Clustering Based Feature Subset Selection System
Abstract: AbstractThis paper presents the feature assortment involve identifying a subset of the majority valuable features with the intention of produce companionable results the same as the inventive complete set of features. A feature assortment system could exist evaluate commencing both the effectiveness and efficiency points of analysis. Although the effectiveness concerns the point in time necessary in the direction of locate a subset of features, the efficiency is linked toward …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 3, Issue 3, 2016 · pp. 1–13 Read article
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An Empirical Study on Evaluating Graph Based Clustering for HD Data Using Attribute Selection
Abstract: An attribute subset selection can be showed as a process of identifying and eliminating or removing a number of irrelevant and surplus attributes (features) because irrelevant attributes do not give predictive accuracy and the surplus attributes provide the information that is already present in the other attributes. Attribute selection involves identifying a subset of the most useful attributes that produces the similar results as the final set of results. An …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 2, 2014 · pp. 33–40 Read article
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Fast Recovery and Privacy Preservation against Global Eavesdropper in Ethernet Network
Abstract: Fast recovery from link failures is a well-studied topic in IP networks. Employing fast recovery in Ethernet networks is complicated as the forwarding is based on destination MAC addresses, which do not have the hierarchical nature similar to those exhibited in Layer 3 in the form of IP-prefixes. Moreover, switches employ backward learning to populate theforwarding table entries. Thus, any fast recovery mechanism in Ethernet networks must be based on …
Published in Journal of Advances in Shell Programming · Vol. 3, Issue 1, 2016 · pp. 12–18 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Doctrine of Signature - A key in Discovering the Therapeutical Effect of Zornia gibbosa Span
Abstract: Abstract According to Doctrine of signatures the herbs that resemble various parts of the body can be used to treat ailments of that part of the body. The theme of natural objects' shapes having significance is very old and can be correlated with “Purushoayam Lokasammitah” (man is epitome of universe) of Ayurveda. In Shatpat Bhrahman, a reference regarding functional correlation of various parts of the trees to that of human …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 3, Issue 1, 2014 · pp. 30–34 Read article
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Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications
Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Massive Data Capturing and Transmission using Big Data Analytics Model with Machine Learning Prediction
Abstract: Deep learning techniques are widely used in many branches of research and engineering, including language processing, image classification, and speech recognition. Similar to this, processing vast amounts of data is restricted by a number of classical data processing approaches. To deal with information progressively with incredible exactness and effectiveness, huge information investigation requests spic and span, complex calculations in light of machine and profound learning methods. Recent research has, however, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 9, Issue 3, 2022 · pp. 23–30 Read article