Search Results - (( parameter optimization method algorithm ) OR ( parallel solution machine algorithm ))
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…The difference between the algorithms is the size of the solution archive. The size of the archive in ACOMV is fixed while in IACOMV, the size of solution archive increases as the optimization procedure progress. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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A new method for decreasing cell-load variation in dynamic cellular manufacturing systems
Published 2016“…In this article, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. …”
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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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Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources
Published 2023“…This paper focuses on solving unrelated parallel machine scheduling with resource constraints (UPMR). …”
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Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem
Published 2008“…Results show that these new sequential and parallel algorithms run faster than the standard sequential and parallel FDTD algorithms. …”
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Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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Flexible job shop scheduling using priority heuristics and genetic algorithm
Published 2010“…The job shop scheduling is very common in practice and uniform machines (parallel machines with different speeds) have been used in job shop environment for flexibility. …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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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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Parallel R-point implicit block method for solving higher order ordinary differential equations directly
Published 2004“…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…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. Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…However, the current meta-heuristic algorithms do not ensure an optimum solution within a reasonable time. …”
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Paralell R-point implicit block method for solving higher order ordinary differential equations directly
Published 2004“…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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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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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of turning parameters using ant colony optimization
Published 2008“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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