Search Results - (( parallel evaluation method algorithm ) OR ( parameter optimization new algorithm ))
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations
Published 2004“…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Enhancing performance of XTS cryptography mode of operation using parallel design
Published 2009“…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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Article -
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
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Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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Book Section -
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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Optimization of turning parameters using ant colony optimization
Published 2008“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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Undergraduates Project Papers -
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023Article -
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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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Conference or Workshop Item -
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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). …”
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Undergraduates Project Papers -
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…Initially, the Grey Wolf algorithm (GWO) is leveraged to exploit its advantages in identifying optimal parameters. …”
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Thesis -
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
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