Search Results - parallel ((((evaluation method) OR (optimization method))) OR (distribution a)) algorithm*
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…In addition, a distributed environment is set up to conduct parallel optimization of the proposed method so that multi-local optimizations could be performed simultaneously. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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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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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems
Published 2017“…To implement the parallel algorithm a distributed parallel computing system using MATLAB Distributed Computing Server (MDCS) is configured. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…The major contribution of this research is to propose MTS method for solving UTSP in both sequential and parallel approach and it is shown that the algorithms are able to produce comparable results for most of the cases from literature and the computational times can be reduced significantly for more than 80% by the parallel execution. …”
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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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Minimizing machining airtime motion with an ant colony algorithm
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…It is built upon the foundation of Differential Evolution for Multi-objective optimization (DEMO) and the weighted sum method (WS), coupled with an innovative ATS repair operator scheme. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…In the partitioning phase, the data is partitioned into smaller subsets that can be clustered in parallel across multiple nodes. The suggested method, implemented in the Databricks cloud platform provides high clustering accuracy, as measured by clustering evaluation metrics such as the silhouette coefficient, cost function, partition index, clustering entropy. …”
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Parallel system for abnormal cell growth prediction based on fast numerical simulation
Published 2010“…The development of the prediction system is the combinations of the parallel algorithms, open source software on Linux environment and distributed multiprocessor system. …”
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Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
Published 2015“…This can be solved by parallelizing the process in cluster environment. Most cluster environment have a variety of computer hardware specification namely heterogeneous environment.Optimizing the resources in heterogeneous environment during parallel processing is not a simple task. …”
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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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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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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The exploration is amplified from roots growth counterparts. In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. …”
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Efficient 3D temperature propagation for laser glass interaction
Published 2008“…A new algorithm in the class of the AGE method is for developed to solve the heat equation in 3 space dimensions laser glass model problem. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…Deep learning has recently emerged as effective methods for machine FDD applications. However, the gradient descent optimization method that is commonly used in deep learning suffers from several limitations, such as high computational cost and local sub-optimal solutions. …”
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