Search Results - (( java implementation path algorithm ) OR ( using graph machine algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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A New Cell Formation Method Considering Operation Sequences And Production Volumes
Published 2013“…The graph theory was employed to develop the algorithm. …”
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An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…In this study, six gene expression datasets are applied to study the effectiveness of the sub-algorithm, directed graph and classifier in SDW in terms of cancer prediction and cancer classification. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In this technique, the graph-based structural models of the fullerenes are proposed using their real structural information. …”
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FROM IMAGE TO GRAPH-BASED DATA FOR PATH PLANNING
Published 2019“…This implementation of graph traversal, statistics and machine learning algorithms were a challenging part to be done. …”
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A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time
Published 2009“…For this problem, we propose a genetic algorithm using an optimised crossover operator designed by an undirected bipartite graph to find an optimal schedule which minimises the total weighted completion time of the jobs in the presence of the sequence independent family setup times. …”
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An analysis of the effect of heterogeneously distributed inertia constant in generation mix power system by using the graph theory and Dijkstra’s Algorithm
Published 2023“…In this paper, we calculate the shortest path between the nodes or substations by using Dijkstra’s algorithm. The betweenness centrality of the node detects the vulnerable nodes in the system from the frequency response point of view.…”
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Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.]
Published 2023“…The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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Genetic algorithms for single machine family scheduling problems with maximum lateness and completion time
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…LACE algorithm is used to schedule and optimize Virtual Machine (VMs) allocation across the servers according to behaviour obtained from locust nature. …”
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Random sampling method of large-scale graph data classification
Published 2024“…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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Exploration of COVID‑19 data in Malaysia through mapper graph
Published 2024“…A support vector-based feature selection and a heuristic approach for fine-tuning parameters internally within the algorithm are conducted. Two anomalous groups of nodes with exceptionally high case numbers emerged respectively for Delta and Omicron dominant periods in the Mapper graphs for daily data. …”
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Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…Poverty mapping and prediction were conducted in North Sumatra to get a precise spatial distribution of poverty, the operation of the poverty model, and forecasting using machine learning (ML). Poverty prediction was conducted using a random forest (RF) algorithm and poverty mapping was conducted using the K-Means algorithm. …”
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