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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Some greedy based algorithms for multi periods degree constrained minimum spanning tree problem
Published 2015“…In this paper we proposed three algorithms by modifying Kruskal’s and Prim’s algorithms. …”
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A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob
Published 2022“…A numerical example related to finding the optimal route that can minimize the cost of solving the medical waste management is provided to show the effectiveness of the Prim's and Kruskal's algorithms with IVBN. As a final step, a comparative study such as interval-valued neutrosophic minimum spanning tree (IVN-MST), interval-valued intuitionistic fuzzy minimum spanning tree (IVIF-MST) and interval-valued fuzzy minimum spanning tree (IVE-MST) is presented to point out the advantages of the proposed method over that of other existing algorithms. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using minimum spanning tree method. …”
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A minimum spanning tree stock market analysis of Malaysia technology companies
Published 2024“…The collected data is the daily closing prices of Malaysia’s top 20 most active companies based on the volume traded in the list of technology companies. The minimum spanning tree was used to construct the network via Kruskal’s algorithm, and the centrality measures of the stocks, such as degree, betweenness, closeness, and eigenvector, were measured to identify influential stocks. …”
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Using modification of Prim's algorithm and GNU Octave and to solve the multiperiods installation problem
Published 2020“…The Minimum Spanning Tree (MST) is one of the famous problems that is used mostly as the backbone in many network design problems. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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11
A minimum spanning tree stock market analysis of Malaysia technology companies
Published 2024“…The collected data is the daily closing prices of Malaysia’s top 20 most active companies based on the volume traded in the list of technology companies. The minimum spanning tree was used to construct the network via Kruskal’s algorithm, and the centrality measures of the stocks, such as degree, betweenness, closeness, and eigenvector, were measured to identify influential stocks. …”
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A minimum spanning tree stock market analysis of Malaysia technology companies
Published 2024“…The collected data is the daily closing prices of Malaysia’s top 20 most ac-tive companies based on the volume traded in the list of technology companies. The minimum spanning tree was used to construct the network via Kruskal’s algorithm, and the centrality measures of the stocks, such as degree, betweenness, closeness, and eigenvector, were measured to identify influential stocks. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Proportional-integral control optimization using imperialist competitive algorithm
Published 2012“…This implies that the ICA can be used to tune the PI control loops for a continuous stirred tank heater with a minimum cost and better response in compare with the GA and the PSO.…”
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Optimum MV Feeder Routing and Substation siting and rating in Distribution Network
Published 2014“…This paper proposes an evolutionary algorithm to determine the optimum distribution substation placement and sizing by using the particle swarm optimization algorithm and optimum feeder routing using modified minimum spanning tree algorithm. …”
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An optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2017“…Therefore, if the resource is from the first group then map the average length task to it and if the choosing resource is from the second group, then map the largest length task to it. The simulation tool used for testing the algorithm is WorkflowSim. We tested averages of execution time span of the proposed algorithm for 10 running times with 200-1000 tasks in 50 or 100 VMs. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm
Published 2024“…Next, the cost aggregation uses minimum spanning tree (MST) segmentation, which equipped with edge preserving properties and noise filtering. …”
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