Search Results - (( development process selection algorithm ) OR ( java simulation optimization algorithm ))
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1
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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2
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job.Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of 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. …”
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3
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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4
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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5
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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6
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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7
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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8
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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9
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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10
Statistical fixed range multiple selection algorithm for peer-to-peer system
Published 2010“…The algorithm is able to reduce the number of rounds needed and increase the success rate of all multiple selections in the selection process compared to the previous multiple selection algorithms proposed by Loo in 2005.…”
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11
Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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Improvement and performance analysis on statistical selection algorithms
Published 2006“…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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13
Static range multiple selection algorithm for peer-to-peer system
Published 2011“…The algorithm is able to reduce the number of messages needed and increases the success rate of all multiple selections in the selection process compared to the previous multiple selection algorithms proposed by Loo in 2005.…”
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14
Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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15
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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16
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…To evaluate the performance of the developed algorithm, the average PSNR value, average search point and average elapsed processing time is calculated. …”
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17
Automated path testing using the negative selection algorithm
Published 2017“…Software testing is an important step in the software development process, accounting for more than 50% of software development cost as it is laborious and time-consuming. …”
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18
Statistical selection algorithm for peer-to-peer system
Published 2008“…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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19
Revisit of statistical selection algorithm for peer-to-peer system
Published 2008“…Over the years, the distributed computing environment has been developed so fast that there’s a need to develop an effective selection algorithm for it. …”
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20
Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. …”
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