Search Results - (( developing selected graph algorithm ) OR ( java implication based algorithm ))
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1
Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
2
VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. …”
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Thesis -
3
Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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4
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. …”
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Monograph -
5
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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6
Laser simulator: a novel search graph-based path planning approach
Published 2018“…A novel technique called laser simulator approach for visibility search graph-based path planning has been developed in this article to determine the optimum collision-free path in unknown environment. …”
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7
An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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Thesis -
8
Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches
Published 2018“…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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9
Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches
Published 2018“…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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10
Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
11
Neural network algorithm-based fall detection modelling
Published 2020“…The type of input source is divided into 4 different types for training. The selection of the model was based on the comparison of optimization epochs, magnitude of validate error or mean square error (MSE), magnitude of correlation performance, the convergence graph in term of MSE performance, accuracy of regression and non-zero value of autocorrelation graph. …”
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12
Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…In addition, this thesis tackles the feature selection problem by designing a novel wrapper feature selection method based on the Hybrid Flower Pollination Algorithm (HFPA). …”
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13
Development of mobile robot and localization system
Published 2014“…The process begins with the mobile robot mechanical design where a selection of wheel types and types of locomotion are selected. …”
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14
AUTOMATIC ROUTE FINDER FOR NEW VISITORS
Published 2006“…This study is based on Dijkstra's algorithm as the algorithm finds the most effective way to traverse an entire graph. …”
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15
Path planning for unmanned aerial vehicles using visibility line-based methods
Published 2011“…This thesis concerns the development of path planning algorithms for unmanned aerial vehicles (UAVs) to avoid obstacles in two- (2D) and three-dimensional (3D) urban environments based on the visibility graph (VG) method. …”
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16
Implication of image processing algorithm in remote sensing and GIS applications
Published 2011“…The traditional ways of solving the problems, have been replaced, by several new algorithms. The selection of an appropriate algorithm for any given chore is an imperative issue because different algorithms are based on the different concepts. …”
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Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem
Published 2018“…Material and methods: To test the proposed technique, selected approximation algorithms have been developed to small graph instances. …”
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Energy efficient path-planning for unmanned aerial vehicle
Published 2022“…The proposed path planning algorithm is called Iterative Elliptical- Convex Visibility Graph (IECoVG) which is based on visibility graph (VG) and Dijkstra’s algorithm. …”
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20
Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles
Published 2025“…This study investigates the physical calibration of a LiDAR sensor mounted on a moving vehicle and its effect on 3D map generation using the HDL Graph SLAM algorithm. HDL Graph SLAM was selected as the offline post-processing method due to its self-correcting functions for estimating and auto-correcting positional errors from LiDAR data. …”
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