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1
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 -
2
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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3
Resource management in grid computing using ant colony optimization
Published 2011“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.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.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.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. …”
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Monograph -
4
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
5
Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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6
Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Practical implications: Because the simulation set‐up is clearly stated, the results of this evaluation can be used as a benchmark for other estimation algorithms. …”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The model was then used to predict glucose concentration profile for a given initial condition of the tapioca hydrolysis process. …”
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Kinetic Parameter Estimation in Alkylation of Benzene with 1-Decene through Hybrid Particle Swarm Optimization
Published 2012“…Activation energies of elementary steps were estimated by using Hybrid Particle Swarm Optimization (HPSO) algorithm. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…In this work, several choices of initialization methods are compared and experimental results indicated that the algorithm is sensitive to the initial value of kinetic parameters. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…The second estimate is obtained by using the tangent line of f (x) at the initial value. …”
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14
A Fuzzy-Neural Approach for Estimation of Depth Map using Focus
Published 2011“…This algorithm is based on Fuzzy-Neural approach using Shape From Focus (SFF). …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…To address the existing theoretical gap, this study focused on developing an objective function that accurately estimates the initial root parameters of Photovoltaic (PV) models. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…There have been various procedures suggested to date, whether through manual or automated selections, to choose the best model.This study nonetheless focuses on an automated selection for multiple equations model with the use of iterative estimation method. In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Single-agent finite impulse response optimizer for numerical optimization problems
Published 2018“…The performance of the SAFIRO algorithm is evaluated using the CEC 2014 Benchmark Test Suite for single-objective optimization and statistically compared with the several well-known metaheuristic optimization algorithms, such as Particle Swarm Optimization algorithm, Genetic Algorithm, and Grey Wolf Optimization algorithm. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model
Published 2021“…Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. …”
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Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali
Published 2017“…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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