Search Results - (( parameters using partial 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 -
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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 -
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. …”
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Novel algorithms of identifying types of Partial Discharges using electrical and non-contact methods / Mohammad Shukri Hapeez
Published 2015“…Two novel algorithms are presented in this wok namely ‘Simple Partial Discharge Identifier (SPDI) and Fundamental Partial Discharge Identifier (FPDI) were developed to overcome the PD identification shortcoming……”
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Book Section -
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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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11
MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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12
Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…It is shown that the proposed SCLAPF algorithm achieves a high gain in EE of more than 120% compared to that obtained by stand-alone partial feedback performance. …”
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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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Novel algorithms of identifying types of partial discharges using electrical and non-contact methods / Mohammad Shukri Hapeez
Published 2015“…Two novel algorithms are presented in this wok namely ‘Simple Partial Discharge Identifier (SPDI) and Fundamental-Partial Discharge Identifier (FPDI) were developed to overcome the PD identification shortcoming. …”
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16
Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming
Published 2023“…The dataset employed for the ANN modeling was obtained using a central composite experimental design. The input parameters consisted of CH4 partial pressure, CO2 partial pressure, and reaction temperature, while the target parameters included the rate of CO and H2 production. …”
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Partial fraction expansion based frequency weighted balanced singular perturbation approximation model reduction technique with error bounds
Published 2016“…For minimization of the frequency weighted approximation error, free parameters are introduced into the algorithm.…”
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Proceeding Paper -
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Nevertheless, conventional PSO suffers from large transient oscillation, slow convergence and tedious parameter tuning when tracking global MPP (GMPP) under partial shading conditions (PSC), leading to poor efficiency and significant power loss. …”
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