Search Results - (( parameters realization _ algorithm ) OR ( java simulation optimization algorithm ))
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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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Monograph -
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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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 -
8
Realization of microcontroller-based polarization control system with genetic algorithm
Published 2009“…To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. …”
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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
Parameter-Less Simulated Kalman Filter
Published 2017“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
Published 2015“…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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16
Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines
Published 2015“…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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Dengue outbreak prediction: hybrid meta-heuristic model
Published 2018“…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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Improving PID controller of motor shaft angular position by using genetic algorithm
Published 2015“…This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. …”
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Application of LSSVM by ABC in energy commodity price forecasting
Published 2014“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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