Search Results - (( based optimization means algorithm ) OR ( parallel distribution process algorithm ))
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Communication and computation rate-cheating problems in divisible load scheduling: revisited
Published 2015“…It is a paradigm in the area of parallel and distributed computing. Based on the DLS the computation and communication can be divided into some arbitrary independent parts, in which each part can be processed independently by a processor. …”
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Investigation of QAM based on mean square error (MSE) channel estimation (CE) for MIMO-OFDM pilot based system / Mohd Ariff Ibrahim
Published 2013“…The Orthogonal Frequency Division Multiplexing (OFDM) is the technique that use for many companies, distributers, researchers, industries and many other signal processing usage for many years. …”
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Multi-criteria divisible load scheduling in binary tree network
Published 2016“…The Divisible Load Theory (DLT) is a paradigm in the area of parallel and distributed computing. Based on the divisible load theory, the computation and communication can be divided into some arbitrary independent parts, in which each part can be processed independently by a processor. …”
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Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
Published 2012“…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
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5
Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…The parallel algorithms of 2-dimensional Partial Differential Equation (PDE) elliptic type for the prediction will be executed using distributed memory of heterogeneous cluster platform on LINUX-based environment. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Geographically distributed heterogeneous resources can execute such workflows in parallel. …”
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The visualization of three dimensional brain tumors' growth on distributed parallel computer systems
Published 2009“…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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Parallel execution of distributed SVM using MPI (CoDLib)
Published 2023“…To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. …”
Conference paper -
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…This manuscript proposes a parallel k means for image processing (PKIP) algorithm using multiprocessing and distributed computing to assess the adhesion failure in WMA and HMA samples subjected to three different moisture sensitivity tests (dry, one, and three freeze-thaw cycles) and fractured by indirect tensile test. …”
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Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition
Published 2018“…Experiments showed that a multi-cores parallel environment is a very appropriate platform for pipeline image processing. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024“…In this paper, a new ABC algorithm called MeanABC is introduced to achieve the search behavior balance via a modified search equation based on the information of the mean of the previous best solutions. …”
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Distributed generation system using parallel inverters supplied by unstable DC source
Published 2009“…The generation of control algorithm for three-phase inverter is implemented in Digital Signal Processing (DSP) boards. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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