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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…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 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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3
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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4
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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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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6
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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7
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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8
Strategies of Handling Different Variables Reduction for LDA
Published 2012“…The variables selection technique with local searching algorithm is manipulated. …”
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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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10
A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…It can effectively enhance the predictive accuracy and execution speed of the CatBoost algorithm model. The third step involves applying the new algorithm to the risk control model for testing and comparison, resulting in the conclusion that the model established by the EBGWO-Catboost algorithm exhibits more advantages compared to models built by other algorithms. …”
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11
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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12
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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15
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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16
A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data
Published 2022“…The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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18
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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19
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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20
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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