Search Results - (( variable _ true algorithm ) OR ( java application optimized algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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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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Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
Published 2018“…The parameters investigated are apparent resistivity ( a ), horizontal location (x) and depth (z) as independent variable; while true resistivity ( t ) is dependent variable.…”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Assessing the simulation performances of multiple model selection algorithm
Published 2015“…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Thesis -
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…During the optimization, the operational constraints of a wellbore such as true vertical depth and casings along with the bounds of tuning variables were utilized. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Three econometric models have been utilised as a testbed for true specification search. The results were divided into four categories where a tight significance level of 1% had contributed a high percentage of all equations in the model contain variables precisely comparable to the true specifications. …”
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Monograph -
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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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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Thesis -
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. The findings from simulation experiments suggested that SURE-Autometrics performed well when the number of equations and number of relevant variables in the true specification model were minimal. …”
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